From b031ef0df193ec4ccc9f526b431dadd2c9790ed4 Mon Sep 17 00:00:00 2001
From: Torch-TensorRT Github Bot <torch-tensorrt.github.bot@nvidia.com>
Date: Tue, 15 Oct 2024 04:22:45 +0000
Subject: [PATCH] docs: [Automated] Regenerating documenation for 2c517be

Signed-off-by: Torch-TensorRT Github Bot <torch-tensorrt.github.bot@nvidia.com>
---
 .../classtorch__tensorrt_1_1DataType.html     |  31 +++---
 ...rch__tensorrt_1_1Device_1_1DeviceType.html |  31 +++---
 .../classtorch__tensorrt_1_1TensorFormat.html |  31 +++---
 ...ensorrt_1_1ptq_1_1Int8CacheCalibrator.html |  31 +++---
 ...ch__tensorrt_1_1ptq_1_1Int8Calibrator.html |  31 +++---
 ...8h_1a18d295a837ac71add5578860b55e5502.html |  31 +++---
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 ...8h_1adad592a7b1b7eed529cdf6acd584c883.html |  31 +++---
 docs/_cpp_api/dir_cpp.html                    |  31 +++---
 docs/_cpp_api/dir_cpp_include.html            |  31 +++---
 .../dir_cpp_include_torch_tensorrt.html       |  31 +++---
 ...ng_1a130f65408ad8cbaee060f05e8db69558.html |  31 +++---
 ...rt_1a3fbe5d72e4fc624dbd038853079620eb.html |  31 +++---
 ..._cpp_include_torch_tensorrt_logging.h.html |  31 +++---
 ...e_cpp_include_torch_tensorrt_macros.h.html |  31 +++---
 ...file_cpp_include_torch_tensorrt_ptq.h.html |  31 +++---
 ...clude_torch_tensorrt_torch_tensorrt.h.html |  31 +++---
 ...ng_1a0593f776f469c20469e2f729fc7861a3.html |  31 +++---
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 ...ng_1af8f3443813315af7901903d25dd495cc.html |  31 +++---
 ...tq_1a226e3c83379d1012cde8578c1c86b16c.html |  31 +++---
 ...tq_1a6186e305f47c1d94b6130ef6c7f7e178.html |  31 +++---
 ...pt_1a5b405fd3bf3c8fc2e2a54cbbab979797.html |  31 +++---
 ...pt_1a6e19490a08fb1553c9dd347a5ae79db9.html |  31 +++---
 ...pt_1a81f9783517335dda877d8cfcf38987c9.html |  31 +++---
 ...pt_1ae8d56472106eeef37fbe51ff7f40c9b2.html |  31 +++---
 ...rt_1ac4ab8313ae72c2c899ea31548b528528.html |  31 +++---
 ...rt_1ad1acd06eaeaffbbcf6e7ebf426891384.html |  31 +++---
 ...rt_1ad6a4ee8ca6c8f6e5519eb1128ec7f4a1.html |  31 +++---
 docs/_cpp_api/namespace_torch_tensorrt.html   |  31 +++---
 .../namespace_torch_tensorrt__logging.html    |  31 +++---
 .../namespace_torch_tensorrt__ptq.html        |  31 +++---
 ...namespace_torch_tensorrt__torchscript.html |  31 +++---
 ..._cpp_include_torch_tensorrt_logging.h.html |  31 +++---
 ...e_cpp_include_torch_tensorrt_macros.h.html |  31 +++---
 ...file_cpp_include_torch_tensorrt_ptq.h.html |  31 +++---
 ...clude_torch_tensorrt_torch_tensorrt.h.html |  31 +++---
 .../structtorch__tensorrt_1_1Device.html      |  31 +++---
 .../structtorch__tensorrt_1_1GraphInputs.html |  31 +++---
 .../structtorch__tensorrt_1_1Input.html       |  31 +++---
 ...ensorrt_1_1torchscript_1_1CompileSpec.html |  31 +++---
 docs/_cpp_api/torch_tensort_cpp.html          |  31 +++---
 docs/_cpp_api/unabridged_orphan.html          |  31 +++---
 .../torch_compile_resnet_example.ipynb        |   2 +-
 .../torch_export_gpt2.py                      |  15 ++-
 .../torch_export_gpt2.ipynb                   |  22 +----
 .../torch_compile_stable_diffusion.py         |   2 +-
 .../_rendered_examples_jupyter.zip            | Bin 118308 -> 117861 bytes
 .../_rendered_examples_python.zip             | Bin 89732 -> 89587 bytes
 .../torch_export_llama2.py                    |  14 +--
 .../torch_export_llama2.ipynb                 |  11 +--
 .../torch_compile_stable_diffusion.ipynb      |   2 +-
 .../torch_compile_transformers_example.ipynb  |   2 +-
 .../torch_compile_resnet_example.py           |   2 +-
 .../torch_compile_transformers_example.py     |   4 +-
 docs/_modules/index.html                      |  31 +++---
 docs/_modules/torch_tensorrt/_Device.html     |  31 +++---
 docs/_modules/torch_tensorrt/_Input.html      |  31 +++---
 docs/_modules/torch_tensorrt/_compile.html    |  31 +++---
 docs/_modules/torch_tensorrt/_enums.html      |  31 +++---
 .../torch_tensorrt/dynamo/_compiler.html      |  31 +++---
 .../torch_tensorrt/dynamo/_exporter.html      |  31 +++---
 .../torch_tensorrt/dynamo/_refit.html         |  31 +++---
 .../torch_tensorrt/dynamo/_settings.html      |  31 +++---
 .../torch_tensorrt/dynamo/_tracer.html        |  31 +++---
 .../runtime/_MutableTorchTensorRTModule.html  |  31 +++---
 .../runtime/_PythonTorchTensorRTModule.html   |  31 +++---
 .../dynamo/runtime/_TorchTensorRTModule.html  |  31 +++---
 docs/_modules/torch_tensorrt/fx/fx2trt.html   |  31 +++---
 .../torch_tensorrt/fx/input_tensor_spec.html  |  31 +++---
 docs/_modules/torch_tensorrt/fx/lower.html    |  31 +++---
 .../torch_tensorrt/fx/trt_module.html         |  31 +++---
 docs/_modules/torch_tensorrt/logging.html     |  31 +++---
 .../runtime/_multi_device_safe_mode.html      |  31 +++---
 .../torch_tensorrt/ts/_compile_spec.html      |  31 +++---
 .../_modules/torch_tensorrt/ts/_compiler.html |  31 +++---
 docs/_modules/torch_tensorrt/ts/ptq.html      |  31 +++---
 docs/_sources/index.rst.txt                   |  25 ++---
 .../_rendered_examples/dynamo/index.rst.txt   |  58 ++++-------
 .../torch_compile_resnet_example.rst.txt      |   2 +-
 .../torch_compile_stable_diffusion.rst.txt    |   2 +-
 ...torch_compile_transformers_example.rst.txt |   4 +-
 .../dynamo/torch_export_gpt2.rst.txt          |  24 ++---
 .../dynamo/torch_export_llama2.rst.txt        |  18 ++--
 .../_rendered_examples/index.rst.txt          |  58 ++++-------
 docs/_sources/tutorials/notebooks.rst.txt     |   5 +-
 docs/_static/documentation_options.js         |   2 +-
 docs/cli/torchtrtc.html                       |  31 +++---
 docs/contributors/conversion.html             |  31 +++---
 docs/contributors/dynamo_converters.html      |  31 +++---
 docs/contributors/lowering.html               |  31 +++---
 docs/contributors/partitioning.html           |  31 +++---
 docs/contributors/phases.html                 |  31 +++---
 docs/contributors/runtime.html                |  31 +++---
 docs/contributors/system_overview.html        |  31 +++---
 docs/contributors/ts_converters.html          |  31 +++---
 docs/contributors/useful_links.html           |  31 +++---
 .../writing_dynamo_aten_lowering_passes.html  |  31 +++---
 docs/dynamo/dynamo_export.html                |  31 +++---
 docs/dynamo/torch_compile.html                |  35 +++----
 docs/fx/getting_started_with_fx_path.html     |  35 +++----
 docs/genindex.html                            |  31 +++---
 docs/getting_started/installation.html        |  31 +++---
 docs/getting_started/quick_start.html         |  31 +++---
 docs/index.html                               |  48 ++++-----
 docs/indices/supported_ops.html               |  31 +++---
 docs/objects.inv                              | Bin 32266 -> 31995 bytes
 docs/py-modindex.html                         |  31 +++---
 docs/py_api/dynamo.html                       |  31 +++---
 docs/py_api/fx.html                           |  31 +++---
 docs/py_api/logging.html                      |  31 +++---
 docs/py_api/ptq.html                          |  31 +++---
 docs/py_api/runtime.html                      |  31 +++---
 docs/py_api/torch_tensorrt.html               |  35 +++----
 docs/py_api/ts.html                           |  33 +++----
 docs/search.html                              |  31 +++---
 docs/searchindex.js                           |   2 +-
 docs/sg_execution_times.html                  |  37 ++++---
 .../pytorch-sphinx-theme/docs/changelog.html  |  31 +++---
 .../docs/configuring.html                     |  31 +++---
 .../pytorch-sphinx-theme/docs/demo/api.html   |  31 +++---
 .../pytorch-sphinx-theme/docs/demo/demo.html  |  33 +++----
 .../docs/demo/lists_tables.html               |  31 +++---
 .../pytorch-sphinx-theme/docs/demo/long.html  |  31 +++---
 .../docs/demo/structure.html                  |  31 +++---
 docs/src/pytorch-sphinx-theme/docs/index.html |  31 +++---
 .../pytorch-sphinx-theme/docs/installing.html |  31 +++---
 ...creating_torchscript_module_in_python.html |  31 +++---
 docs/ts/getting_started_with_cpp_api.html     |  31 +++---
 docs/ts/getting_started_with_python_api.html  |  31 +++---
 docs/ts/ptq.html                              |  31 +++---
 .../ts/torchscript_frontend_from_pytorch.html |  31 +++---
 .../dynamo/converter_overloading.html         |  35 +++----
 .../dynamo/custom_kernel_plugins.html         |  35 +++----
 .../dynamo/engine_caching_bert_example.html   |  31 +++---
 .../dynamo/engine_caching_example.html        |  31 +++---
 .../_rendered_examples/dynamo/index.html      |  93 +++++++-----------
 .../mutable_torchtrt_module_example.html      |  39 ++++----
 .../dynamo/refit_engine_example.html          |  35 +++----
 .../dynamo/torch_compile_advanced_usage.html  |  31 +++---
 .../dynamo/torch_compile_resnet_example.html  |  47 +++++----
 .../torch_compile_stable_diffusion.html       |  47 +++++----
 .../torch_compile_transformers_example.html   |  49 +++++----
 .../dynamo/torch_export_cudagraphs.html       |  39 ++++----
 .../dynamo/torch_export_gpt2.html             |  67 ++++++-------
 .../dynamo/torch_export_llama2.html           |  69 +++++++------
 .../_rendered_examples/dynamo/vgg16_ptq.html  |  31 +++---
 docs/tutorials/_rendered_examples/index.html  |  87 ++++++----------
 docs/tutorials/notebooks.html                 |  50 +++++-----
 .../serving_torch_tensorrt_with_triton.html   |  43 ++++----
 docs/user_guide/dynamic_shapes.html           |  31 +++---
 docs/user_guide/mixed_precision.html          |  31 +++---
 docs/user_guide/runtime.html                  |  31 +++---
 docs/user_guide/saving_models.html            |  31 +++---
 docs/user_guide/torch_tensorrt_explained.html |  31 +++---
 docs/user_guide/using_dla.html                |  31 +++---
 165 files changed, 2224 insertions(+), 2763 deletions(-)

diff --git a/docs/_cpp_api/classtorch__tensorrt_1_1DataType.html b/docs/_cpp_api/classtorch__tensorrt_1_1DataType.html
index dd5f0ea0a0..fefe4e482a 100644
--- a/docs/_cpp_api/classtorch__tensorrt_1_1DataType.html
+++ b/docs/_cpp_api/classtorch__tensorrt_1_1DataType.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Class DataType &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Class DataType &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/classtorch__tensorrt_1_1Device_1_1DeviceType.html b/docs/_cpp_api/classtorch__tensorrt_1_1Device_1_1DeviceType.html
index 6df355a23e..dfb210b55c 100644
--- a/docs/_cpp_api/classtorch__tensorrt_1_1Device_1_1DeviceType.html
+++ b/docs/_cpp_api/classtorch__tensorrt_1_1Device_1_1DeviceType.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Class Device::DeviceType &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Class Device::DeviceType &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/classtorch__tensorrt_1_1TensorFormat.html b/docs/_cpp_api/classtorch__tensorrt_1_1TensorFormat.html
index 1e742c8858..ef47addfaa 100644
--- a/docs/_cpp_api/classtorch__tensorrt_1_1TensorFormat.html
+++ b/docs/_cpp_api/classtorch__tensorrt_1_1TensorFormat.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Class TensorFormat &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Class TensorFormat &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/classtorch__tensorrt_1_1ptq_1_1Int8CacheCalibrator.html b/docs/_cpp_api/classtorch__tensorrt_1_1ptq_1_1Int8CacheCalibrator.html
index ed1ea18288..9b6b3dbb7f 100644
--- a/docs/_cpp_api/classtorch__tensorrt_1_1ptq_1_1Int8CacheCalibrator.html
+++ b/docs/_cpp_api/classtorch__tensorrt_1_1ptq_1_1Int8CacheCalibrator.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Template Class Int8CacheCalibrator &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Template Class Int8CacheCalibrator &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/classtorch__tensorrt_1_1ptq_1_1Int8Calibrator.html b/docs/_cpp_api/classtorch__tensorrt_1_1ptq_1_1Int8Calibrator.html
index cefa00b7f2..54ad25a97c 100644
--- a/docs/_cpp_api/classtorch__tensorrt_1_1ptq_1_1Int8Calibrator.html
+++ b/docs/_cpp_api/classtorch__tensorrt_1_1ptq_1_1Int8Calibrator.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Template Class Int8Calibrator &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Template Class Int8Calibrator &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/define_macros_8h_1a18d295a837ac71add5578860b55e5502.html b/docs/_cpp_api/define_macros_8h_1a18d295a837ac71add5578860b55e5502.html
index 043a615aec..80ab3374ad 100644
--- a/docs/_cpp_api/define_macros_8h_1a18d295a837ac71add5578860b55e5502.html
+++ b/docs/_cpp_api/define_macros_8h_1a18d295a837ac71add5578860b55e5502.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Define STR &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Define STR &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/define_macros_8h_1a282fd3c0b1c3a215148ae372070e1268.html b/docs/_cpp_api/define_macros_8h_1a282fd3c0b1c3a215148ae372070e1268.html
index 8aab792e3c..6099cd4238 100644
--- a/docs/_cpp_api/define_macros_8h_1a282fd3c0b1c3a215148ae372070e1268.html
+++ b/docs/_cpp_api/define_macros_8h_1a282fd3c0b1c3a215148ae372070e1268.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Define TORCH_TENSORRT_PATCH_VERSION &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Define TORCH_TENSORRT_PATCH_VERSION &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/define_macros_8h_1a31398a6d4d27e28817afb0f0139e909e.html b/docs/_cpp_api/define_macros_8h_1a31398a6d4d27e28817afb0f0139e909e.html
index 957d9293a7..2439b9d7c4 100644
--- a/docs/_cpp_api/define_macros_8h_1a31398a6d4d27e28817afb0f0139e909e.html
+++ b/docs/_cpp_api/define_macros_8h_1a31398a6d4d27e28817afb0f0139e909e.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Define TORCH_TENSORRT_MAJOR_VERSION &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Define TORCH_TENSORRT_MAJOR_VERSION &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/define_macros_8h_1a35703561b26b1a9d2738ad7d58b27827.html b/docs/_cpp_api/define_macros_8h_1a35703561b26b1a9d2738ad7d58b27827.html
index 9804cb2851..d08e9b3724 100644
--- a/docs/_cpp_api/define_macros_8h_1a35703561b26b1a9d2738ad7d58b27827.html
+++ b/docs/_cpp_api/define_macros_8h_1a35703561b26b1a9d2738ad7d58b27827.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Define TORCH_TENSORRT_MINOR_VERSION &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Define TORCH_TENSORRT_MINOR_VERSION &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/define_macros_8h_1abd1465eb38256d3f22cc1426b23d516b.html b/docs/_cpp_api/define_macros_8h_1abd1465eb38256d3f22cc1426b23d516b.html
index e0080e7724..3e9ba6bc17 100644
--- a/docs/_cpp_api/define_macros_8h_1abd1465eb38256d3f22cc1426b23d516b.html
+++ b/docs/_cpp_api/define_macros_8h_1abd1465eb38256d3f22cc1426b23d516b.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Define TORCHTRT_API &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Define TORCHTRT_API &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/define_macros_8h_1abe87b341f562fd1cf40b7672e4d759da.html b/docs/_cpp_api/define_macros_8h_1abe87b341f562fd1cf40b7672e4d759da.html
index 4c1ba1e459..129726fa1a 100644
--- a/docs/_cpp_api/define_macros_8h_1abe87b341f562fd1cf40b7672e4d759da.html
+++ b/docs/_cpp_api/define_macros_8h_1abe87b341f562fd1cf40b7672e4d759da.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Define XSTR &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Define XSTR &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/define_macros_8h_1ad19939408f7be171a74a89928b36eb59.html b/docs/_cpp_api/define_macros_8h_1ad19939408f7be171a74a89928b36eb59.html
index b5d8bce2cc..0686c37902 100644
--- a/docs/_cpp_api/define_macros_8h_1ad19939408f7be171a74a89928b36eb59.html
+++ b/docs/_cpp_api/define_macros_8h_1ad19939408f7be171a74a89928b36eb59.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Define TORCHTRT_HIDDEN &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Define TORCHTRT_HIDDEN &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/define_macros_8h_1adad592a7b1b7eed529cdf6acd584c883.html b/docs/_cpp_api/define_macros_8h_1adad592a7b1b7eed529cdf6acd584c883.html
index f62866c87f..e180a05377 100644
--- a/docs/_cpp_api/define_macros_8h_1adad592a7b1b7eed529cdf6acd584c883.html
+++ b/docs/_cpp_api/define_macros_8h_1adad592a7b1b7eed529cdf6acd584c883.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Define TORCH_TENSORRT_VERSION &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Define TORCH_TENSORRT_VERSION &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/dir_cpp.html b/docs/_cpp_api/dir_cpp.html
index 1dc9f93a3d..64f9020907 100644
--- a/docs/_cpp_api/dir_cpp.html
+++ b/docs/_cpp_api/dir_cpp.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Directory cpp &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Directory cpp &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/dir_cpp_include.html b/docs/_cpp_api/dir_cpp_include.html
index 8d487abd55..6f40b740a9 100644
--- a/docs/_cpp_api/dir_cpp_include.html
+++ b/docs/_cpp_api/dir_cpp_include.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Directory include &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Directory include &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/dir_cpp_include_torch_tensorrt.html b/docs/_cpp_api/dir_cpp_include_torch_tensorrt.html
index a41562c80b..3836287950 100644
--- a/docs/_cpp_api/dir_cpp_include_torch_tensorrt.html
+++ b/docs/_cpp_api/dir_cpp_include_torch_tensorrt.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Directory torch_tensorrt &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Directory torch_tensorrt &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/enum_namespacetorch__tensorrt_1_1logging_1a130f65408ad8cbaee060f05e8db69558.html b/docs/_cpp_api/enum_namespacetorch__tensorrt_1_1logging_1a130f65408ad8cbaee060f05e8db69558.html
index 9e0bef85d4..be0a310fbf 100644
--- a/docs/_cpp_api/enum_namespacetorch__tensorrt_1_1logging_1a130f65408ad8cbaee060f05e8db69558.html
+++ b/docs/_cpp_api/enum_namespacetorch__tensorrt_1_1logging_1a130f65408ad8cbaee060f05e8db69558.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Enum Level &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Enum Level &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/enum_namespacetorch__tensorrt_1a3fbe5d72e4fc624dbd038853079620eb.html b/docs/_cpp_api/enum_namespacetorch__tensorrt_1a3fbe5d72e4fc624dbd038853079620eb.html
index 82688bbf99..ed2986beaf 100644
--- a/docs/_cpp_api/enum_namespacetorch__tensorrt_1a3fbe5d72e4fc624dbd038853079620eb.html
+++ b/docs/_cpp_api/enum_namespacetorch__tensorrt_1a3fbe5d72e4fc624dbd038853079620eb.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Enum EngineCapability &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Enum EngineCapability &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/file_cpp_include_torch_tensorrt_logging.h.html b/docs/_cpp_api/file_cpp_include_torch_tensorrt_logging.h.html
index f9f20e6923..11e427e13c 100644
--- a/docs/_cpp_api/file_cpp_include_torch_tensorrt_logging.h.html
+++ b/docs/_cpp_api/file_cpp_include_torch_tensorrt_logging.h.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>File logging.h &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>File logging.h &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/file_cpp_include_torch_tensorrt_macros.h.html b/docs/_cpp_api/file_cpp_include_torch_tensorrt_macros.h.html
index aff61c357a..b90f4c39f4 100644
--- a/docs/_cpp_api/file_cpp_include_torch_tensorrt_macros.h.html
+++ b/docs/_cpp_api/file_cpp_include_torch_tensorrt_macros.h.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>File macros.h &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>File macros.h &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/file_cpp_include_torch_tensorrt_ptq.h.html b/docs/_cpp_api/file_cpp_include_torch_tensorrt_ptq.h.html
index 4e3e32ac07..cf90cad5c2 100644
--- a/docs/_cpp_api/file_cpp_include_torch_tensorrt_ptq.h.html
+++ b/docs/_cpp_api/file_cpp_include_torch_tensorrt_ptq.h.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>File ptq.h &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>File ptq.h &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/file_cpp_include_torch_tensorrt_torch_tensorrt.h.html b/docs/_cpp_api/file_cpp_include_torch_tensorrt_torch_tensorrt.h.html
index 55693d4236..a2e9b6c3f2 100644
--- a/docs/_cpp_api/file_cpp_include_torch_tensorrt_torch_tensorrt.h.html
+++ b/docs/_cpp_api/file_cpp_include_torch_tensorrt_torch_tensorrt.h.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>File torch_tensorrt.h &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>File torch_tensorrt.h &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a0593f776f469c20469e2f729fc7861a3.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a0593f776f469c20469e2f729fc7861a3.html
index cdbc971e1b..47d9382559 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a0593f776f469c20469e2f729fc7861a3.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a0593f776f469c20469e2f729fc7861a3.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Function torch_tensorrt::logging::get_logging_prefix &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Function torch_tensorrt::logging::get_logging_prefix &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a0c012cb374addd90eb1f42eaec570650.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a0c012cb374addd90eb1f42eaec570650.html
index e7ecd1ead6..d718ab87c7 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a0c012cb374addd90eb1f42eaec570650.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a0c012cb374addd90eb1f42eaec570650.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Function torch_tensorrt::logging::get_reportable_log_level &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Function torch_tensorrt::logging::get_reportable_log_level &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a56e110feaaba2c3fd44bd201fd21a76a.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a56e110feaaba2c3fd44bd201fd21a76a.html
index b3e92c9c63..76f15d606c 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a56e110feaaba2c3fd44bd201fd21a76a.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a56e110feaaba2c3fd44bd201fd21a76a.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Function torch_tensorrt::logging::get_is_colored_output_on &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Function torch_tensorrt::logging::get_is_colored_output_on &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a7cb50492421ea9de4e3db895819df6f2.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a7cb50492421ea9de4e3db895819df6f2.html
index 4fceca8387..3c22247ad6 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a7cb50492421ea9de4e3db895819df6f2.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1a7cb50492421ea9de4e3db895819df6f2.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Function torch_tensorrt::logging::set_reportable_log_level &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Function torch_tensorrt::logging::set_reportable_log_level &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1ac46ac0901cb97e3ae6e93b45f24e90b8.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1ac46ac0901cb97e3ae6e93b45f24e90b8.html
index 4588bab5ac..97c5a87486 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1ac46ac0901cb97e3ae6e93b45f24e90b8.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1ac46ac0901cb97e3ae6e93b45f24e90b8.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Function torch_tensorrt::logging::log &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Function torch_tensorrt::logging::log &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1ad2efd47b6c3689e58ccc595680579ae5.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1ad2efd47b6c3689e58ccc595680579ae5.html
index 03a14fd43e..f5cc717713 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1ad2efd47b6c3689e58ccc595680579ae5.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1ad2efd47b6c3689e58ccc595680579ae5.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Function torch_tensorrt::logging::set_is_colored_output_on &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Function torch_tensorrt::logging::set_is_colored_output_on &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1af8f3443813315af7901903d25dd495cc.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1af8f3443813315af7901903d25dd495cc.html
index 0f11a63959..5c9d4b1264 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1af8f3443813315af7901903d25dd495cc.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1logging_1af8f3443813315af7901903d25dd495cc.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Function torch_tensorrt::logging::set_logging_prefix &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Function torch_tensorrt::logging::set_logging_prefix &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1ptq_1a226e3c83379d1012cde8578c1c86b16c.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1ptq_1a226e3c83379d1012cde8578c1c86b16c.html
index 358267fa7b..45ef6c88ce 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1ptq_1a226e3c83379d1012cde8578c1c86b16c.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1ptq_1a226e3c83379d1012cde8578c1c86b16c.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Template Function torch_tensorrt::ptq::make_int8_cache_calibrator &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Template Function torch_tensorrt::ptq::make_int8_cache_calibrator &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1ptq_1a6186e305f47c1d94b6130ef6c7f7e178.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1ptq_1a6186e305f47c1d94b6130ef6c7f7e178.html
index d611774b68..8a21fee2ff 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1ptq_1a6186e305f47c1d94b6130ef6c7f7e178.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1ptq_1a6186e305f47c1d94b6130ef6c7f7e178.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Template Function torch_tensorrt::ptq::make_int8_calibrator &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Template Function torch_tensorrt::ptq::make_int8_calibrator &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1a5b405fd3bf3c8fc2e2a54cbbab979797.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1a5b405fd3bf3c8fc2e2a54cbbab979797.html
index 72b0289721..a596a9d015 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1a5b405fd3bf3c8fc2e2a54cbbab979797.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1a5b405fd3bf3c8fc2e2a54cbbab979797.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Function torch_tensorrt::torchscript::check_method_operator_support &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Function torch_tensorrt::torchscript::check_method_operator_support &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1a6e19490a08fb1553c9dd347a5ae79db9.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1a6e19490a08fb1553c9dd347a5ae79db9.html
index e78ec14057..af21e2fd5a 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1a6e19490a08fb1553c9dd347a5ae79db9.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1a6e19490a08fb1553c9dd347a5ae79db9.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Function torch_tensorrt::torchscript::compile &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Function torch_tensorrt::torchscript::compile &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1a81f9783517335dda877d8cfcf38987c9.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1a81f9783517335dda877d8cfcf38987c9.html
index 75988e7b3f..d544a0590d 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1a81f9783517335dda877d8cfcf38987c9.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1a81f9783517335dda877d8cfcf38987c9.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Function torch_tensorrt::torchscript::embed_engine_in_new_module &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Function torch_tensorrt::torchscript::embed_engine_in_new_module &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1ae8d56472106eeef37fbe51ff7f40c9b2.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1ae8d56472106eeef37fbe51ff7f40c9b2.html
index c49e4fe18a..df3e447ccd 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1ae8d56472106eeef37fbe51ff7f40c9b2.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1_1torchscript_1ae8d56472106eeef37fbe51ff7f40c9b2.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Function torch_tensorrt::torchscript::convert_method_to_trt_engine &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Function torch_tensorrt::torchscript::convert_method_to_trt_engine &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1ac4ab8313ae72c2c899ea31548b528528.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1ac4ab8313ae72c2c899ea31548b528528.html
index 66b1fbc1f9..ae9a8d586e 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1ac4ab8313ae72c2c899ea31548b528528.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1ac4ab8313ae72c2c899ea31548b528528.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Function torch_tensorrt::get_build_info &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Function torch_tensorrt::get_build_info &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1ad1acd06eaeaffbbcf6e7ebf426891384.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1ad1acd06eaeaffbbcf6e7ebf426891384.html
index ed7a0ff356..1d986ace58 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1ad1acd06eaeaffbbcf6e7ebf426891384.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1ad1acd06eaeaffbbcf6e7ebf426891384.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Function torch_tensorrt::set_device &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Function torch_tensorrt::set_device &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/function_namespacetorch__tensorrt_1ad6a4ee8ca6c8f6e5519eb1128ec7f4a1.html b/docs/_cpp_api/function_namespacetorch__tensorrt_1ad6a4ee8ca6c8f6e5519eb1128ec7f4a1.html
index 4a9cc3948b..c39bedc9cc 100644
--- a/docs/_cpp_api/function_namespacetorch__tensorrt_1ad6a4ee8ca6c8f6e5519eb1128ec7f4a1.html
+++ b/docs/_cpp_api/function_namespacetorch__tensorrt_1ad6a4ee8ca6c8f6e5519eb1128ec7f4a1.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Function torch_tensorrt::dump_build_info &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Function torch_tensorrt::dump_build_info &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/namespace_torch_tensorrt.html b/docs/_cpp_api/namespace_torch_tensorrt.html
index 03c97d77d4..1d5d7b82f4 100644
--- a/docs/_cpp_api/namespace_torch_tensorrt.html
+++ b/docs/_cpp_api/namespace_torch_tensorrt.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Namespace torch_tensorrt &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Namespace torch_tensorrt &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/namespace_torch_tensorrt__logging.html b/docs/_cpp_api/namespace_torch_tensorrt__logging.html
index 2fc654fbec..4ee232e1e7 100644
--- a/docs/_cpp_api/namespace_torch_tensorrt__logging.html
+++ b/docs/_cpp_api/namespace_torch_tensorrt__logging.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Namespace torch_tensorrt::logging &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Namespace torch_tensorrt::logging &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/namespace_torch_tensorrt__ptq.html b/docs/_cpp_api/namespace_torch_tensorrt__ptq.html
index d0a5841287..02df82e956 100644
--- a/docs/_cpp_api/namespace_torch_tensorrt__ptq.html
+++ b/docs/_cpp_api/namespace_torch_tensorrt__ptq.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Namespace torch_tensorrt::ptq &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Namespace torch_tensorrt::ptq &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/namespace_torch_tensorrt__torchscript.html b/docs/_cpp_api/namespace_torch_tensorrt__torchscript.html
index b8de17ab87..50e6f82e8a 100644
--- a/docs/_cpp_api/namespace_torch_tensorrt__torchscript.html
+++ b/docs/_cpp_api/namespace_torch_tensorrt__torchscript.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Namespace torch_tensorrt::torchscript &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Namespace torch_tensorrt::torchscript &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_logging.h.html b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_logging.h.html
index 18ed4bc57b..a91a9daeef 100644
--- a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_logging.h.html
+++ b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_logging.h.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Program Listing for File logging.h &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Program Listing for File logging.h &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_macros.h.html b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_macros.h.html
index 8de4907e0d..379a7e9116 100644
--- a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_macros.h.html
+++ b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_macros.h.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Program Listing for File macros.h &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Program Listing for File macros.h &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_ptq.h.html b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_ptq.h.html
index 02eb4d45a7..5efe6c5ee3 100644
--- a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_ptq.h.html
+++ b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_ptq.h.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Program Listing for File ptq.h &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Program Listing for File ptq.h &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_torch_tensorrt.h.html b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_torch_tensorrt.h.html
index 1d8d673c26..b0a261c467 100644
--- a/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_torch_tensorrt.h.html
+++ b/docs/_cpp_api/program_listing_file_cpp_include_torch_tensorrt_torch_tensorrt.h.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Program Listing for File torch_tensorrt.h &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Program Listing for File torch_tensorrt.h &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/structtorch__tensorrt_1_1Device.html b/docs/_cpp_api/structtorch__tensorrt_1_1Device.html
index 1ed4e56127..fed41b4bb8 100644
--- a/docs/_cpp_api/structtorch__tensorrt_1_1Device.html
+++ b/docs/_cpp_api/structtorch__tensorrt_1_1Device.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Struct Device &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Struct Device &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/structtorch__tensorrt_1_1GraphInputs.html b/docs/_cpp_api/structtorch__tensorrt_1_1GraphInputs.html
index 8a0c6276f0..e32c670333 100644
--- a/docs/_cpp_api/structtorch__tensorrt_1_1GraphInputs.html
+++ b/docs/_cpp_api/structtorch__tensorrt_1_1GraphInputs.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Struct GraphInputs &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Struct GraphInputs &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/structtorch__tensorrt_1_1Input.html b/docs/_cpp_api/structtorch__tensorrt_1_1Input.html
index e8c52e9872..58e3d038c7 100644
--- a/docs/_cpp_api/structtorch__tensorrt_1_1Input.html
+++ b/docs/_cpp_api/structtorch__tensorrt_1_1Input.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Struct Input &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Struct Input &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/structtorch__tensorrt_1_1torchscript_1_1CompileSpec.html b/docs/_cpp_api/structtorch__tensorrt_1_1torchscript_1_1CompileSpec.html
index ca8428f9cb..18f9fb08b0 100644
--- a/docs/_cpp_api/structtorch__tensorrt_1_1torchscript_1_1CompileSpec.html
+++ b/docs/_cpp_api/structtorch__tensorrt_1_1torchscript_1_1CompileSpec.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Struct CompileSpec &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Struct CompileSpec &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/torch_tensort_cpp.html b/docs/_cpp_api/torch_tensort_cpp.html
index 92aee27d82..d9919dcc9a 100644
--- a/docs/_cpp_api/torch_tensort_cpp.html
+++ b/docs/_cpp_api/torch_tensort_cpp.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Torch-TensorRT C++ API &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Torch-TensorRT C++ API &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_cpp_api/unabridged_orphan.html b/docs/_cpp_api/unabridged_orphan.html
index f9653efe77..6cde3de016 100644
--- a/docs/_cpp_api/unabridged_orphan.html
+++ b/docs/_cpp_api/unabridged_orphan.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Full API &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Full API &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_downloads/0daf1d0af656cac7b808856b71e6616f/torch_compile_resnet_example.ipynb b/docs/_downloads/0daf1d0af656cac7b808856b71e6616f/torch_compile_resnet_example.ipynb
index 935722964f..e6c161f892 100644
--- a/docs/_downloads/0daf1d0af656cac7b808856b71e6616f/torch_compile_resnet_example.ipynb
+++ b/docs/_downloads/0daf1d0af656cac7b808856b71e6616f/torch_compile_resnet_example.ipynb
@@ -4,7 +4,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n\n# Compiling ResNet using the Torch-TensorRT `torch.compile` Backend\n\nThis interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a ResNet model.\n"
+        "\n\n# Compiling ResNet with dynamic shapes using the `torch.compile` backend\n\nThis interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a ResNet model.\n"
       ]
     },
     {
diff --git a/docs/_downloads/2a9ac10f2667047a7f398d1593b7ca33/torch_export_gpt2.py b/docs/_downloads/2a9ac10f2667047a7f398d1593b7ca33/torch_export_gpt2.py
index f9229e420c..cea0f3adf2 100644
--- a/docs/_downloads/2a9ac10f2667047a7f398d1593b7ca33/torch_export_gpt2.py
+++ b/docs/_downloads/2a9ac10f2667047a7f398d1593b7ca33/torch_export_gpt2.py
@@ -1,10 +1,10 @@
 """
 .. _torch_export_gpt2:
 
-Compiling GPT2 using the Torch-TensorRT with dynamo backend
+Compiling GPT2 using the dynamo backend
 ==========================================================
 
-This interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo backend on a GPT2 model."""
+This script illustrates Torch-TensorRT workflow with dynamo backend on popular GPT2 model."""
 
 # %%
 # Imports and Model Definition
@@ -88,13 +88,10 @@
     tokenizer.decode(trt_gen_tokens[0], skip_special_tokens=True),
 )
 
-# %%
-# The output sentences should look like
-# =============================
-# Pytorch model generated text:  What is parallel programming ?
+# Prompt : What is parallel programming ?
 
-# The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that
 # =============================
-# TensorRT model generated text:  What is parallel programming ?
+# Pytorch model generated text: The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that
 
-# The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that
+# =============================
+# TensorRT model generated text: The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that
diff --git a/docs/_downloads/34421db2f2a82ea2b3d9a9cc85624784/torch_export_gpt2.ipynb b/docs/_downloads/34421db2f2a82ea2b3d9a9cc85624784/torch_export_gpt2.ipynb
index 6b09a33d5b..d14952a8ed 100644
--- a/docs/_downloads/34421db2f2a82ea2b3d9a9cc85624784/torch_export_gpt2.ipynb
+++ b/docs/_downloads/34421db2f2a82ea2b3d9a9cc85624784/torch_export_gpt2.ipynb
@@ -4,7 +4,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n\n# Compiling GPT2 using the Torch-TensorRT with dynamo backend\n\nThis interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo backend on a GPT2 model.\n"
+        "\n\n# Compiling GPT2 using the dynamo backend\n\nThis script illustrates Torch-TensorRT workflow with dynamo backend on popular GPT2 model.\n"
       ]
     },
     {
@@ -87,25 +87,7 @@
       },
       "outputs": [],
       "source": [
-        "print(\"=============================\")\nprint(\n    \"Pytorch model generated text: \",\n    tokenizer.decode(pyt_gen_tokens[0], skip_special_tokens=True),\n)\nprint(\"=============================\")\nprint(\n    \"TensorRT model generated text: \",\n    tokenizer.decode(trt_gen_tokens[0], skip_special_tokens=True),\n)"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "# The output sentences should look like\nPytorch model generated text:  What is parallel programming ?\n\n"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "collapsed": false
-      },
-      "outputs": [],
-      "source": [
-        "# The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that\n# =============================\n# TensorRT model generated text:  What is parallel programming ?\n\n# The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that"
+        "print(\"=============================\")\nprint(\n    \"Pytorch model generated text: \",\n    tokenizer.decode(pyt_gen_tokens[0], skip_special_tokens=True),\n)\nprint(\"=============================\")\nprint(\n    \"TensorRT model generated text: \",\n    tokenizer.decode(trt_gen_tokens[0], skip_special_tokens=True),\n)\n\n# Prompt : What is parallel programming ?\n\n# =============================\n# Pytorch model generated text: The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that\n\n# =============================\n# TensorRT model generated text: The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that"
       ]
     }
   ],
diff --git a/docs/_downloads/46b3e6febaab06324aa2715896895544/torch_compile_stable_diffusion.py b/docs/_downloads/46b3e6febaab06324aa2715896895544/torch_compile_stable_diffusion.py
index a0b725572b..fe49da74d1 100644
--- a/docs/_downloads/46b3e6febaab06324aa2715896895544/torch_compile_stable_diffusion.py
+++ b/docs/_downloads/46b3e6febaab06324aa2715896895544/torch_compile_stable_diffusion.py
@@ -1,7 +1,7 @@
 """
 .. _torch_compile_stable_diffusion:
 
-Torch Compile Stable Diffusion
+Compiling Stable Diffusion model using the `torch.compile` backend
 ======================================================
 
 This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a Stable Diffusion model. A sample output is featured below:
diff --git a/docs/_downloads/6a6052d9668b2cb8332d349d328e21c1/_rendered_examples_jupyter.zip b/docs/_downloads/6a6052d9668b2cb8332d349d328e21c1/_rendered_examples_jupyter.zip
index 1327b06a5c5277bb828d310888c0f04595e404eb..850b2ffccd8896ebd3a61b7ab96df485f910d632 100644
GIT binary patch
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diff --git a/docs/_downloads/798cda8f83bd9f5e2cc93f329a04332c/_rendered_examples_python.zip b/docs/_downloads/798cda8f83bd9f5e2cc93f329a04332c/_rendered_examples_python.zip
index 36611286f083481320476d9760143cad3c5ad1e9..ba5bf56b3b42b3c76437eaef250eba6a4a3216a1 100644
GIT binary patch
delta 951
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diff --git a/docs/_downloads/7b7004dc2ea6f839be532665e16e0426/torch_export_llama2.py b/docs/_downloads/7b7004dc2ea6f839be532665e16e0426/torch_export_llama2.py
index 11a0c93276..5cfd1ed61c 100644
--- a/docs/_downloads/7b7004dc2ea6f839be532665e16e0426/torch_export_llama2.py
+++ b/docs/_downloads/7b7004dc2ea6f839be532665e16e0426/torch_export_llama2.py
@@ -1,10 +1,10 @@
 """
 .. _torch_export_llama2:
 
-Compiling Llama2 using the Torch-TensorRT with dynamo backend
+Compiling Llama2 using the dynamo backend
 ==========================================================
 
-This interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo backend on a Llama2 model."""
+This script illustrates Torch-TensorRT workflow with dynamo backend on popular Llama2 model."""
 
 # %%
 # Imports and Model Definition
@@ -91,9 +91,11 @@
     )[0],
 )
 
-# %%
-# The output sentences should look like
+
+# Prompt : What is dynamic programming?
+
 # =============================
-# Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and
+# Pytorch model generated text: Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and
+
 # =============================
-# TensorRT model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and
+# TensorRT model generated text: Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and
diff --git a/docs/_downloads/9e148ac48490c84d381ee281904f3226/torch_export_llama2.ipynb b/docs/_downloads/9e148ac48490c84d381ee281904f3226/torch_export_llama2.ipynb
index 171465315f..a90e28b6a3 100644
--- a/docs/_downloads/9e148ac48490c84d381ee281904f3226/torch_export_llama2.ipynb
+++ b/docs/_downloads/9e148ac48490c84d381ee281904f3226/torch_export_llama2.ipynb
@@ -4,7 +4,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n\n# Compiling Llama2 using the Torch-TensorRT with dynamo backend\n\nThis interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo backend on a Llama2 model.\n"
+        "\n\n# Compiling Llama2 using the dynamo backend\n\nThis script illustrates Torch-TensorRT workflow with dynamo backend on popular Llama2 model.\n"
       ]
     },
     {
@@ -94,14 +94,7 @@
       },
       "outputs": [],
       "source": [
-        "print(\"=============================\")\nprint(\n    \"Pytorch model generated text: \",\n    tokenizer.batch_decode(\n        pyt_gen_tokens, skip_special_tokens=True, clean_up_tokenization_spaces=False\n    )[0],\n)\nprint(\"=============================\")\nprint(\n    \"TensorRT model generated text: \",\n    tokenizer.batch_decode(\n        trt_gen_tokens,\n        skip_special_tokens=True,\n        clean_up_tokenization_spaces=False,\n    )[0],\n)"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "metadata": {},
-      "source": [
-        "# The output sentences should look like\nPytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and\n=============================\nTensorRT model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and\n\n"
+        "print(\"=============================\")\nprint(\n    \"Pytorch model generated text: \",\n    tokenizer.batch_decode(\n        pyt_gen_tokens, skip_special_tokens=True, clean_up_tokenization_spaces=False\n    )[0],\n)\nprint(\"=============================\")\nprint(\n    \"TensorRT model generated text: \",\n    tokenizer.batch_decode(\n        trt_gen_tokens,\n        skip_special_tokens=True,\n        clean_up_tokenization_spaces=False,\n    )[0],\n)\n\n\n# Prompt : What is dynamic programming?\n\n# =============================\n# Pytorch model generated text: Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and\n\n# =============================\n# TensorRT model generated text: Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and"
       ]
     }
   ],
diff --git a/docs/_downloads/b776287bc876f7ce24942b82a66beb05/torch_compile_stable_diffusion.ipynb b/docs/_downloads/b776287bc876f7ce24942b82a66beb05/torch_compile_stable_diffusion.ipynb
index bc86c3dbd0..eac19f81a2 100644
--- a/docs/_downloads/b776287bc876f7ce24942b82a66beb05/torch_compile_stable_diffusion.ipynb
+++ b/docs/_downloads/b776287bc876f7ce24942b82a66beb05/torch_compile_stable_diffusion.ipynb
@@ -4,7 +4,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n\n# Torch Compile Stable Diffusion\n\nThis interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a Stable Diffusion model. A sample output is featured below:\n\n<img src=\"file://tutorials/images/majestic_castle.png\" width=\"512px\" height=\"512px\" scale=\"50 %\" align=\"right\">\n"
+        "\n\n# Compiling Stable Diffusion model using the `torch.compile` backend\n\nThis interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a Stable Diffusion model. A sample output is featured below:\n\n<img src=\"file://tutorials/images/majestic_castle.png\" width=\"512px\" height=\"512px\" scale=\"50 %\" align=\"right\">\n"
       ]
     },
     {
diff --git a/docs/_downloads/ce102e287ddb5744f0a1364e8c0c7f68/torch_compile_transformers_example.ipynb b/docs/_downloads/ce102e287ddb5744f0a1364e8c0c7f68/torch_compile_transformers_example.ipynb
index 15fb754e33..74998c0164 100644
--- a/docs/_downloads/ce102e287ddb5744f0a1364e8c0c7f68/torch_compile_transformers_example.ipynb
+++ b/docs/_downloads/ce102e287ddb5744f0a1364e8c0c7f68/torch_compile_transformers_example.ipynb
@@ -4,7 +4,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n\n# Compiling a Transformer using torch.compile and TensorRT\n\nThis interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a transformer-based model.\n"
+        "\n\n# Compiling BERT using the `torch.compile` backend\n\nThis interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a BERT model.\n"
       ]
     },
     {
diff --git a/docs/_downloads/d6e1bb6ec5f884994554d9d12e37a0f6/torch_compile_resnet_example.py b/docs/_downloads/d6e1bb6ec5f884994554d9d12e37a0f6/torch_compile_resnet_example.py
index 420c5390d3..f852d60158 100644
--- a/docs/_downloads/d6e1bb6ec5f884994554d9d12e37a0f6/torch_compile_resnet_example.py
+++ b/docs/_downloads/d6e1bb6ec5f884994554d9d12e37a0f6/torch_compile_resnet_example.py
@@ -1,7 +1,7 @@
 """
 .. _torch_compile_resnet:
 
-Compiling ResNet using the Torch-TensorRT `torch.compile` Backend
+Compiling ResNet with dynamic shapes using the `torch.compile` backend
 ==========================================================
 
 This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a ResNet model."""
diff --git a/docs/_downloads/dfa60e8f9850fd7761f3e7da81304d32/torch_compile_transformers_example.py b/docs/_downloads/dfa60e8f9850fd7761f3e7da81304d32/torch_compile_transformers_example.py
index 01d46e96f6..221ecd4fd1 100644
--- a/docs/_downloads/dfa60e8f9850fd7761f3e7da81304d32/torch_compile_transformers_example.py
+++ b/docs/_downloads/dfa60e8f9850fd7761f3e7da81304d32/torch_compile_transformers_example.py
@@ -1,10 +1,10 @@
 """
 .. _torch_compile_transformer:
 
-Compiling a Transformer using torch.compile and TensorRT
+Compiling BERT using the `torch.compile` backend
 ==============================================================
 
-This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a transformer-based model."""
+This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a BERT model."""
 
 # %%
 # Imports and Model Definition
diff --git a/docs/_modules/index.html b/docs/_modules/index.html
index 83cadc6bf4..3615078f82 100644
--- a/docs/_modules/index.html
+++ b/docs/_modules/index.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Overview: module code &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Overview: module code &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/_Device.html b/docs/_modules/torch_tensorrt/_Device.html
index ef99208912..4097ae403d 100644
--- a/docs/_modules/torch_tensorrt/_Device.html
+++ b/docs/_modules/torch_tensorrt/_Device.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt._Device &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt._Device &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/_Input.html b/docs/_modules/torch_tensorrt/_Input.html
index 329508c277..afc80b18fc 100644
--- a/docs/_modules/torch_tensorrt/_Input.html
+++ b/docs/_modules/torch_tensorrt/_Input.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt._Input &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt._Input &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/_compile.html b/docs/_modules/torch_tensorrt/_compile.html
index 46c40fab86..bbb05e45ad 100644
--- a/docs/_modules/torch_tensorrt/_compile.html
+++ b/docs/_modules/torch_tensorrt/_compile.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt._compile &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt._compile &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/_enums.html b/docs/_modules/torch_tensorrt/_enums.html
index 0eddca6ae1..679e76add5 100644
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   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt._enums &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt._enums &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/dynamo/_compiler.html b/docs/_modules/torch_tensorrt/dynamo/_compiler.html
index e6692da541..3bbf46f7a1 100644
--- a/docs/_modules/torch_tensorrt/dynamo/_compiler.html
+++ b/docs/_modules/torch_tensorrt/dynamo/_compiler.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.dynamo._compiler &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.dynamo._compiler &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/dynamo/_exporter.html b/docs/_modules/torch_tensorrt/dynamo/_exporter.html
index 2151ccf4b1..b4768ff859 100644
--- a/docs/_modules/torch_tensorrt/dynamo/_exporter.html
+++ b/docs/_modules/torch_tensorrt/dynamo/_exporter.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.dynamo._exporter &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.dynamo._exporter &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
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diff --git a/docs/_modules/torch_tensorrt/dynamo/_refit.html b/docs/_modules/torch_tensorrt/dynamo/_refit.html
index c76378723c..4e2a2521e1 100644
--- a/docs/_modules/torch_tensorrt/dynamo/_refit.html
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@@ -9,7 +9,7 @@
   
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-  <title>torch_tensorrt.dynamo._refit &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.dynamo._refit &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
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index dc8cf04759..a26d1286bc 100644
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   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.dynamo._settings &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.dynamo._settings &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
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@@ -317,6 +317,11 @@
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 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
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-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
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-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
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-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
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-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
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diff --git a/docs/_modules/torch_tensorrt/dynamo/_tracer.html b/docs/_modules/torch_tensorrt/dynamo/_tracer.html
index acf142d96e..9a9757f466 100644
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   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.dynamo._tracer &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.dynamo._tracer &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
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-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.html b/docs/_modules/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.html
index 787c5f42d5..d308954efe 100644
--- a/docs/_modules/torch_tensorrt/dynamo/runtime/_MutableTorchTensorRTModule.html
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@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.dynamo.runtime._MutableTorchTensorRTModule &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
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-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/notebooks.html">Legacy notebooks</a></li>
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 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
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diff --git a/docs/_modules/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.html b/docs/_modules/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.html
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--- a/docs/_modules/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.html
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+  <title>torch_tensorrt.dynamo.runtime._PythonTorchTensorRTModule &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
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@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
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 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
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-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
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diff --git a/docs/_modules/torch_tensorrt/dynamo/runtime/_TorchTensorRTModule.html b/docs/_modules/torch_tensorrt/dynamo/runtime/_TorchTensorRTModule.html
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@@ -9,7 +9,7 @@
   
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-  <title>torch_tensorrt.dynamo.runtime._TorchTensorRTModule &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.dynamo.runtime._TorchTensorRTModule &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
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@@ -317,6 +317,11 @@
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 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
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-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/fx/fx2trt.html b/docs/_modules/torch_tensorrt/fx/fx2trt.html
index 1d04f6da2d..34033c7fc1 100644
--- a/docs/_modules/torch_tensorrt/fx/fx2trt.html
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@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.fx.fx2trt &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.fx.fx2trt &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
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@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
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-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
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-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
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-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/fx/input_tensor_spec.html b/docs/_modules/torch_tensorrt/fx/input_tensor_spec.html
index 1d4f4033e3..52fd9deda4 100644
--- a/docs/_modules/torch_tensorrt/fx/input_tensor_spec.html
+++ b/docs/_modules/torch_tensorrt/fx/input_tensor_spec.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.fx.input_tensor_spec &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.fx.input_tensor_spec &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/fx/lower.html b/docs/_modules/torch_tensorrt/fx/lower.html
index 23884dbb3e..5af2085b5c 100644
--- a/docs/_modules/torch_tensorrt/fx/lower.html
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@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.fx.lower &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.fx.lower &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
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 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/fx/trt_module.html b/docs/_modules/torch_tensorrt/fx/trt_module.html
index 80483f2411..8950295f0e 100644
--- a/docs/_modules/torch_tensorrt/fx/trt_module.html
+++ b/docs/_modules/torch_tensorrt/fx/trt_module.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.fx.trt_module &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.fx.trt_module &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/logging.html b/docs/_modules/torch_tensorrt/logging.html
index 4645268363..c2633900ce 100644
--- a/docs/_modules/torch_tensorrt/logging.html
+++ b/docs/_modules/torch_tensorrt/logging.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.logging &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.logging &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
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diff --git a/docs/_modules/torch_tensorrt/runtime/_multi_device_safe_mode.html b/docs/_modules/torch_tensorrt/runtime/_multi_device_safe_mode.html
index afe353e511..f7df228f6f 100644
--- a/docs/_modules/torch_tensorrt/runtime/_multi_device_safe_mode.html
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@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.runtime._multi_device_safe_mode &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.runtime._multi_device_safe_mode &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
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 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/ts/_compile_spec.html b/docs/_modules/torch_tensorrt/ts/_compile_spec.html
index 53e6b7cdd7..00d1431fac 100644
--- a/docs/_modules/torch_tensorrt/ts/_compile_spec.html
+++ b/docs/_modules/torch_tensorrt/ts/_compile_spec.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.ts._compile_spec &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.ts._compile_spec &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/ts/_compiler.html b/docs/_modules/torch_tensorrt/ts/_compiler.html
index 89c6d8297e..996656d4f9 100644
--- a/docs/_modules/torch_tensorrt/ts/_compiler.html
+++ b/docs/_modules/torch_tensorrt/ts/_compiler.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.ts._compiler &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.ts._compiler &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_modules/torch_tensorrt/ts/ptq.html b/docs/_modules/torch_tensorrt/ts/ptq.html
index f3244728c3..197bd4c2d4 100644
--- a/docs/_modules/torch_tensorrt/ts/ptq.html
+++ b/docs/_modules/torch_tensorrt/ts/ptq.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.ts.ptq &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.ts.ptq &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/_sources/index.rst.txt b/docs/_sources/index.rst.txt
index eaf547d60e..b3d90055cf 100644
--- a/docs/_sources/index.rst.txt
+++ b/docs/_sources/index.rst.txt
@@ -54,6 +54,11 @@ User Guide
    tutorials/_rendered_examples/dynamo/vgg16_ptq
    tutorials/_rendered_examples/dynamo/engine_caching_example
    tutorials/_rendered_examples/dynamo/refit_engine_example
+   tutorials/serving_torch_tensorrt_with_triton
+   tutorials/_rendered_examples/dynamo/torch_export_cudagraphs
+   tutorials/_rendered_examples/dynamo/converter_overloading
+   tutorials/_rendered_examples/dynamo/custom_kernel_plugins
+   tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example
 
 Dynamo Frontend
 ----------------
@@ -99,30 +104,28 @@ FX Frontend
 
    fx/getting_started_with_fx_path
 
-Tutorials
+Model Zoo
 ------------
-* :ref:`torch_tensorrt_tutorials`
-* :ref:`serving_torch_tensorrt_with_triton`
+* :ref:`torch_compile_resnet`
+* :ref:`torch_compile_transformer`
+* :ref:`torch_compile_stable_diffusion`
+* :ref:`torch_export_gpt2`
+* :ref:`torch_export_llama2`
 * :ref:`notebooks`
 
 .. toctree::
-   :caption: Tutorials
+   :caption: Model Zoo
    :maxdepth: 3
    :hidden:
-
-   tutorials/serving_torch_tensorrt_with_triton
-   tutorials/notebooks
+   
    tutorials/_rendered_examples/dynamo/torch_compile_resnet_example
    tutorials/_rendered_examples/dynamo/torch_compile_transformers_example
    tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion
-   tutorials/_rendered_examples/dynamo/torch_export_cudagraphs
-   tutorials/_rendered_examples/dynamo/converter_overloading
-   tutorials/_rendered_examples/dynamo/custom_kernel_plugins
    tutorials/_rendered_examples/distributed_inference/data_parallel_gpt2
    tutorials/_rendered_examples/distributed_inference/data_parallel_stable_diffusion
-   tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example
    tutorials/_rendered_examples/dynamo/torch_export_gpt2
    tutorials/_rendered_examples/dynamo/torch_export_llama2
+   tutorials/notebooks
 
 Python API Documentation
 ------------------------
diff --git a/docs/_sources/tutorials/_rendered_examples/dynamo/index.rst.txt b/docs/_sources/tutorials/_rendered_examples/dynamo/index.rst.txt
index 17b6bc2a85..cb28b2b62b 100644
--- a/docs/_sources/tutorials/_rendered_examples/dynamo/index.rst.txt
+++ b/docs/_sources/tutorials/_rendered_examples/dynamo/index.rst.txt
@@ -2,13 +2,9 @@
 
 .. _sphx_glr_tutorials__rendered_examples_dynamo:
 
-.. _torch_compile:
+.. _torch_tensorrt_examples:
 
-Torch-TensorRT Examples
-====================================
-
-Please refer to the following examples which demonstrate the usage of different features of Torch-TensorRT. We also provide
-examples of Torch-TensorRT compilation of select computer vision and language models.
+Here we provide examples of Torch-TensorRT compilation of popular computer vision and language models.
 
 Dependencies
 ------------------------------------
@@ -20,18 +16,6 @@ Please install the following external dependencies (assuming you already have co
     pip install -r requirements.txt
 
 
-Compiler Features
-------------------------------------
-* :ref:`torch_compile_advanced_usage`: Advanced usage including making a custom backend to use directly with the ``torch.compile`` API
-* :ref:`torch_export_cudagraphs`: Using the Cudagraphs integration with `ir="dynamo"`
-* :ref:`converter_overloading`: How to write custom converters and overload existing ones
-* :ref:`custom_kernel_plugins`: Creating a plugin to use a custom kernel inside TensorRT engines
-* :ref:`refit_engine_example`: Refitting a compiled TensorRT Graph Module with updated weights
-* :ref:`mutable_torchtrt_module_example`: Compile, use, and modify TensorRT Graph Module with MutableTorchTensorRTModule
-* :ref:`vgg16_fp8_ptq`: Compiling a VGG16 model with FP8 and PTQ using ``torch.compile``
-* :ref:`engine_caching_example`: Utilizing engine caching to speed up compilation times
-* :ref:`engine_caching_bert_example`: Demonstrating engine caching on BERT
-
 Model Zoo
 ------------------------------------
 * :ref:`torch_compile_resnet`: Compiling a ResNet model using the Torch Compile Frontend for ``torch_tensorrt.compile``
@@ -59,7 +43,7 @@ Model Zoo
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Torch Compile Stable Diffusion</div>
+      <div class="sphx-glr-thumbnail-title">Compiling Stable Diffusion model using the torch.compile backend</div>
     </div>
 
 
@@ -110,7 +94,7 @@ Model Zoo
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Compiling a Transformer using torch.compile and TensorRT</div>
+      <div class="sphx-glr-thumbnail-title">Compiling BERT using the torch.compile backend</div>
     </div>
 
 
@@ -150,69 +134,69 @@ Model Zoo
 
 .. raw:: html
 
-    <div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo back...">
+    <div class="sphx-glr-thumbcontainer" tooltip="We are going to demonstrate how we can easily use Mutable Torch TensorRT Module to compile, int...">
 
 .. only:: html
 
-  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_torch_export_llama2_thumb.png
+  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_mutable_torchtrt_module_example_thumb.png
     :alt:
 
-  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_torch_export_llama2.py`
+  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_mutable_torchtrt_module_example.py`
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Compiling Llama2 using the Torch-TensorRT with dynamo backend</div>
+      <div class="sphx-glr-thumbnail-title">Mutable Torch TensorRT Module</div>
     </div>
 
 
 .. raw:: html
 
-    <div class="sphx-glr-thumbcontainer" tooltip="We are going to demonstrate how we can easily use Mutable Torch TensorRT Module to compile, int...">
+    <div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with torch.compi...">
 
 .. only:: html
 
-  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_mutable_torchtrt_module_example_thumb.png
+  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_torch_compile_resnet_example_thumb.png
     :alt:
 
-  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_mutable_torchtrt_module_example.py`
+  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_torch_compile_resnet_example.py`
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Mutable Torch TensorRT Module</div>
+      <div class="sphx-glr-thumbnail-title">Compiling ResNet with dynamic shapes using the torch.compile backend</div>
     </div>
 
 
 .. raw:: html
 
-    <div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with torch.compi...">
+    <div class="sphx-glr-thumbcontainer" tooltip="This script illustrates Torch-TensorRT workflow with dynamo backend on popular GPT2 model.">
 
 .. only:: html
 
-  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_torch_compile_resnet_example_thumb.png
+  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_torch_export_gpt2_thumb.png
     :alt:
 
-  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_torch_compile_resnet_example.py`
+  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_torch_export_gpt2.py`
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Compiling ResNet using the Torch-TensorRT torch.compile Backend</div>
+      <div class="sphx-glr-thumbnail-title">Compiling GPT2 using the dynamo backend</div>
     </div>
 
 
 .. raw:: html
 
-    <div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo back...">
+    <div class="sphx-glr-thumbcontainer" tooltip="This script illustrates Torch-TensorRT workflow with dynamo backend on popular Llama2 model.">
 
 .. only:: html
 
-  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_torch_export_gpt2_thumb.png
+  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_torch_export_llama2_thumb.png
     :alt:
 
-  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_torch_export_gpt2.py`
+  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_torch_export_llama2.py`
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Compiling GPT2 using the Torch-TensorRT with dynamo backend</div>
+      <div class="sphx-glr-thumbnail-title">Compiling Llama2 using the dynamo backend</div>
     </div>
 
 
@@ -298,10 +282,10 @@ Model Zoo
    /tutorials/_rendered_examples/dynamo/torch_compile_transformers_example
    /tutorials/_rendered_examples/dynamo/torch_compile_advanced_usage
    /tutorials/_rendered_examples/dynamo/engine_caching_bert_example
-   /tutorials/_rendered_examples/dynamo/torch_export_llama2
    /tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example
    /tutorials/_rendered_examples/dynamo/torch_compile_resnet_example
    /tutorials/_rendered_examples/dynamo/torch_export_gpt2
+   /tutorials/_rendered_examples/dynamo/torch_export_llama2
    /tutorials/_rendered_examples/dynamo/converter_overloading
    /tutorials/_rendered_examples/dynamo/vgg16_ptq
    /tutorials/_rendered_examples/dynamo/engine_caching_example
diff --git a/docs/_sources/tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.rst.txt b/docs/_sources/tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.rst.txt
index a223ad9d2d..ca4980988e 100644
--- a/docs/_sources/tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.rst.txt
+++ b/docs/_sources/tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.rst.txt
@@ -20,7 +20,7 @@
 
 .. _torch_compile_resnet:
 
-Compiling ResNet using the Torch-TensorRT `torch.compile` Backend
+Compiling ResNet with dynamic shapes using the `torch.compile` backend
 ==========================================================
 
 This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a ResNet model.
diff --git a/docs/_sources/tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.rst.txt b/docs/_sources/tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.rst.txt
index eb8f53aa4b..30873dcde5 100644
--- a/docs/_sources/tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.rst.txt
+++ b/docs/_sources/tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.rst.txt
@@ -20,7 +20,7 @@
 
 .. _torch_compile_stable_diffusion:
 
-Torch Compile Stable Diffusion
+Compiling Stable Diffusion model using the `torch.compile` backend
 ======================================================
 
 This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a Stable Diffusion model. A sample output is featured below:
diff --git a/docs/_sources/tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.rst.txt b/docs/_sources/tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.rst.txt
index b362e42447..8021e43c34 100644
--- a/docs/_sources/tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.rst.txt
+++ b/docs/_sources/tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.rst.txt
@@ -20,10 +20,10 @@
 
 .. _torch_compile_transformer:
 
-Compiling a Transformer using torch.compile and TensorRT
+Compiling BERT using the `torch.compile` backend
 ==============================================================
 
-This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a transformer-based model.
+This interactive script is intended as a sample of the Torch-TensorRT workflow with `torch.compile` on a BERT model.
 
 .. GENERATED FROM PYTHON SOURCE LINES 10-12
 
diff --git a/docs/_sources/tutorials/_rendered_examples/dynamo/torch_export_gpt2.rst.txt b/docs/_sources/tutorials/_rendered_examples/dynamo/torch_export_gpt2.rst.txt
index c692ccc2d3..db986554f2 100644
--- a/docs/_sources/tutorials/_rendered_examples/dynamo/torch_export_gpt2.rst.txt
+++ b/docs/_sources/tutorials/_rendered_examples/dynamo/torch_export_gpt2.rst.txt
@@ -20,10 +20,10 @@
 
 .. _torch_export_gpt2:
 
-Compiling GPT2 using the Torch-TensorRT with dynamo backend
+Compiling GPT2 using the dynamo backend
 ==========================================================
 
-This interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo backend on a GPT2 model.
+This script illustrates Torch-TensorRT workflow with dynamo backend on popular GPT2 model.
 
 .. GENERATED FROM PYTHON SOURCE LINES 10-12
 
@@ -123,7 +123,7 @@ Compilation with `Torch-TensorRT` using dynamo backend and generate TensorRT out
 Decode the output sentences of PyTorch and TensorRT
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-.. GENERATED FROM PYTHON SOURCE LINES 80-91
+.. GENERATED FROM PYTHON SOURCE LINES 80-98
 
 .. code-block:: python
 
@@ -138,23 +138,13 @@ Decode the output sentences of PyTorch and TensorRT
         tokenizer.decode(trt_gen_tokens[0], skip_special_tokens=True),
     )
 
+    # Prompt : What is parallel programming ?
 
-.. GENERATED FROM PYTHON SOURCE LINES 92-95
-
-The output sentences should look like
-=============================
-Pytorch model generated text:  What is parallel programming ?
-
-.. GENERATED FROM PYTHON SOURCE LINES 95-101
-
-.. code-block:: python
-
-
-    # The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that
     # =============================
-    # TensorRT model generated text:  What is parallel programming ?
+    # Pytorch model generated text: The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that
 
-    # The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that
+    # =============================
+    # TensorRT model generated text: The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that
 
 
 .. rst-class:: sphx-glr-timing
diff --git a/docs/_sources/tutorials/_rendered_examples/dynamo/torch_export_llama2.rst.txt b/docs/_sources/tutorials/_rendered_examples/dynamo/torch_export_llama2.rst.txt
index 5c86d845a4..c142aa76d4 100644
--- a/docs/_sources/tutorials/_rendered_examples/dynamo/torch_export_llama2.rst.txt
+++ b/docs/_sources/tutorials/_rendered_examples/dynamo/torch_export_llama2.rst.txt
@@ -20,10 +20,10 @@
 
 .. _torch_export_llama2:
 
-Compiling Llama2 using the Torch-TensorRT with dynamo backend
+Compiling Llama2 using the dynamo backend
 ==========================================================
 
-This interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo backend on a Llama2 model.
+This script illustrates Torch-TensorRT workflow with dynamo backend on popular Llama2 model.
 
 .. GENERATED FROM PYTHON SOURCE LINES 10-12
 
@@ -123,7 +123,7 @@ Compilation with `Torch-TensorRT` using dynamo backend and generate TensorRT out
 Decode the output sentences of PyTorch and TensorRT
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-.. GENERATED FROM PYTHON SOURCE LINES 77-94
+.. GENERATED FROM PYTHON SOURCE LINES 77-102
 
 .. code-block:: python
 
@@ -145,13 +145,13 @@ Decode the output sentences of PyTorch and TensorRT
     )
 
 
-.. GENERATED FROM PYTHON SOURCE LINES 95-100
+    # Prompt : What is dynamic programming?
 
-The output sentences should look like
-=============================
-Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and
-=============================
-TensorRT model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and
+    # =============================
+    # Pytorch model generated text: Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and
+
+    # =============================
+    # TensorRT model generated text: Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and
 
 
 .. rst-class:: sphx-glr-timing
diff --git a/docs/_sources/tutorials/_rendered_examples/index.rst.txt b/docs/_sources/tutorials/_rendered_examples/index.rst.txt
index 1f397896e1..0acd41a003 100644
--- a/docs/_sources/tutorials/_rendered_examples/index.rst.txt
+++ b/docs/_sources/tutorials/_rendered_examples/index.rst.txt
@@ -5,10 +5,6 @@
 Torch-TensorRT Tutorials
 ===========================
 
-The user guide covers the basic concepts and usage of Torch-TensorRT.
-We also provide a number of tutorials to explore specific usecases and advanced concepts
-
-
 
 .. raw:: html
 
@@ -20,11 +16,7 @@ We also provide a number of tutorials to explore specific usecases and advanced
     </div>
 
 
-Torch-TensorRT Examples
-====================================
-
-Please refer to the following examples which demonstrate the usage of different features of Torch-TensorRT. We also provide
-examples of Torch-TensorRT compilation of select computer vision and language models.
+Here we provide examples of Torch-TensorRT compilation of popular computer vision and language models.
 
 Dependencies
 ------------------------------------
@@ -36,18 +28,6 @@ Please install the following external dependencies (assuming you already have co
     pip install -r requirements.txt
 
 
-Compiler Features
-------------------------------------
-* :ref:`torch_compile_advanced_usage`: Advanced usage including making a custom backend to use directly with the ``torch.compile`` API
-* :ref:`torch_export_cudagraphs`: Using the Cudagraphs integration with `ir="dynamo"`
-* :ref:`converter_overloading`: How to write custom converters and overload existing ones
-* :ref:`custom_kernel_plugins`: Creating a plugin to use a custom kernel inside TensorRT engines
-* :ref:`refit_engine_example`: Refitting a compiled TensorRT Graph Module with updated weights
-* :ref:`mutable_torchtrt_module_example`: Compile, use, and modify TensorRT Graph Module with MutableTorchTensorRTModule
-* :ref:`vgg16_fp8_ptq`: Compiling a VGG16 model with FP8 and PTQ using ``torch.compile``
-* :ref:`engine_caching_example`: Utilizing engine caching to speed up compilation times
-* :ref:`engine_caching_bert_example`: Demonstrating engine caching on BERT
-
 Model Zoo
 ------------------------------------
 * :ref:`torch_compile_resnet`: Compiling a ResNet model using the Torch Compile Frontend for ``torch_tensorrt.compile``
@@ -75,7 +55,7 @@ Model Zoo
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Torch Compile Stable Diffusion</div>
+      <div class="sphx-glr-thumbnail-title">Compiling Stable Diffusion model using the torch.compile backend</div>
     </div>
 
 
@@ -126,7 +106,7 @@ Model Zoo
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Compiling a Transformer using torch.compile and TensorRT</div>
+      <div class="sphx-glr-thumbnail-title">Compiling BERT using the torch.compile backend</div>
     </div>
 
 
@@ -166,69 +146,69 @@ Model Zoo
 
 .. raw:: html
 
-    <div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo back...">
+    <div class="sphx-glr-thumbcontainer" tooltip="We are going to demonstrate how we can easily use Mutable Torch TensorRT Module to compile, int...">
 
 .. only:: html
 
-  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_torch_export_llama2_thumb.png
+  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_mutable_torchtrt_module_example_thumb.png
     :alt:
 
-  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_torch_export_llama2.py`
+  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_mutable_torchtrt_module_example.py`
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Compiling Llama2 using the Torch-TensorRT with dynamo backend</div>
+      <div class="sphx-glr-thumbnail-title">Mutable Torch TensorRT Module</div>
     </div>
 
 
 .. raw:: html
 
-    <div class="sphx-glr-thumbcontainer" tooltip="We are going to demonstrate how we can easily use Mutable Torch TensorRT Module to compile, int...">
+    <div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with torch.compi...">
 
 .. only:: html
 
-  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_mutable_torchtrt_module_example_thumb.png
+  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_torch_compile_resnet_example_thumb.png
     :alt:
 
-  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_mutable_torchtrt_module_example.py`
+  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_torch_compile_resnet_example.py`
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Mutable Torch TensorRT Module</div>
+      <div class="sphx-glr-thumbnail-title">Compiling ResNet with dynamic shapes using the torch.compile backend</div>
     </div>
 
 
 .. raw:: html
 
-    <div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with torch.compi...">
+    <div class="sphx-glr-thumbcontainer" tooltip="This script illustrates Torch-TensorRT workflow with dynamo backend on popular GPT2 model.">
 
 .. only:: html
 
-  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_torch_compile_resnet_example_thumb.png
+  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_torch_export_gpt2_thumb.png
     :alt:
 
-  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_torch_compile_resnet_example.py`
+  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_torch_export_gpt2.py`
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Compiling ResNet using the Torch-TensorRT torch.compile Backend</div>
+      <div class="sphx-glr-thumbnail-title">Compiling GPT2 using the dynamo backend</div>
     </div>
 
 
 .. raw:: html
 
-    <div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo back...">
+    <div class="sphx-glr-thumbcontainer" tooltip="This script illustrates Torch-TensorRT workflow with dynamo backend on popular Llama2 model.">
 
 .. only:: html
 
-  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_torch_export_gpt2_thumb.png
+  .. image:: /tutorials/_rendered_examples/dynamo/images/thumb/sphx_glr_torch_export_llama2_thumb.png
     :alt:
 
-  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_torch_export_gpt2.py`
+  :ref:`sphx_glr_tutorials__rendered_examples_dynamo_torch_export_llama2.py`
 
 .. raw:: html
 
-      <div class="sphx-glr-thumbnail-title">Compiling GPT2 using the Torch-TensorRT with dynamo backend</div>
+      <div class="sphx-glr-thumbnail-title">Compiling Llama2 using the dynamo backend</div>
     </div>
 
 
diff --git a/docs/_sources/tutorials/notebooks.rst.txt b/docs/_sources/tutorials/notebooks.rst.txt
index 14737a8f63..509676d83a 100644
--- a/docs/_sources/tutorials/notebooks.rst.txt
+++ b/docs/_sources/tutorials/notebooks.rst.txt
@@ -1,10 +1,9 @@
 .. _notebooks:
 
-Example notebooks
+Legacy notebooks
 ===================
 
-There exists a number of notebooks which cover specific using specific features and models
-with Torch-TensorRT
+There exists a number of notebooks which demonstrate different model conversions / features / frontends available within Torch-TensorRT
 
 Notebooks
 ------------
diff --git a/docs/_static/documentation_options.js b/docs/_static/documentation_options.js
index 9b22b62560..d58ad172d7 100644
--- a/docs/_static/documentation_options.js
+++ b/docs/_static/documentation_options.js
@@ -1,6 +1,6 @@
 var DOCUMENTATION_OPTIONS = {
     URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'),
-    VERSION: 'v2.6.0.dev0+743fdbd',
+    VERSION: 'v2.6.0.dev0+2c517be',
     LANGUAGE: 'en',
     COLLAPSE_INDEX: false,
     BUILDER: 'html',
diff --git a/docs/cli/torchtrtc.html b/docs/cli/torchtrtc.html
index 776ba00304..743fdf4da5 100644
--- a/docs/cli/torchtrtc.html
+++ b/docs/cli/torchtrtc.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torchtrtc &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torchtrtc &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/contributors/conversion.html b/docs/contributors/conversion.html
index 46bfc363c4..ef5b6309c3 100644
--- a/docs/contributors/conversion.html
+++ b/docs/contributors/conversion.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Conversion Phase &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Conversion Phase &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/contributors/dynamo_converters.html b/docs/contributors/dynamo_converters.html
index 9a2d0ea8d7..bd36c498bc 100644
--- a/docs/contributors/dynamo_converters.html
+++ b/docs/contributors/dynamo_converters.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Writing Dynamo Converters &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Writing Dynamo Converters &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/contributors/lowering.html b/docs/contributors/lowering.html
index 95c458ae35..f2d3220f6d 100644
--- a/docs/contributors/lowering.html
+++ b/docs/contributors/lowering.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Lowering Phase &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Lowering Phase &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/contributors/partitioning.html b/docs/contributors/partitioning.html
index 17885f5bc4..d7d35c1738 100644
--- a/docs/contributors/partitioning.html
+++ b/docs/contributors/partitioning.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Partitioning Phase &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Partitioning Phase &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/contributors/phases.html b/docs/contributors/phases.html
index a05ec986b4..1a1d0fe9ab 100644
--- a/docs/contributors/phases.html
+++ b/docs/contributors/phases.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Compiler Phases &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Compiler Phases &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/contributors/runtime.html b/docs/contributors/runtime.html
index 9b253e17d3..5975edfb16 100644
--- a/docs/contributors/runtime.html
+++ b/docs/contributors/runtime.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Runtime Phase &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Runtime Phase &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/contributors/system_overview.html b/docs/contributors/system_overview.html
index b71b7f7da3..e2c8110d59 100644
--- a/docs/contributors/system_overview.html
+++ b/docs/contributors/system_overview.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>System Overview &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>System Overview &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/contributors/ts_converters.html b/docs/contributors/ts_converters.html
index d6a4ab8350..1b7be0e91d 100644
--- a/docs/contributors/ts_converters.html
+++ b/docs/contributors/ts_converters.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Writing TorchScript Converters &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Writing TorchScript Converters &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/contributors/useful_links.html b/docs/contributors/useful_links.html
index c781406839..1beb8d0c46 100644
--- a/docs/contributors/useful_links.html
+++ b/docs/contributors/useful_links.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Useful Links for Torch-TensorRT Development &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Useful Links for Torch-TensorRT Development &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/contributors/writing_dynamo_aten_lowering_passes.html b/docs/contributors/writing_dynamo_aten_lowering_passes.html
index 4f71bd6ffe..407121e822 100644
--- a/docs/contributors/writing_dynamo_aten_lowering_passes.html
+++ b/docs/contributors/writing_dynamo_aten_lowering_passes.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Writing Dynamo ATen Lowering Passes &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Writing Dynamo ATen Lowering Passes &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/dynamo/dynamo_export.html b/docs/dynamo/dynamo_export.html
index e23e73f061..9f9e08496c 100644
--- a/docs/dynamo/dynamo_export.html
+++ b/docs/dynamo/dynamo_export.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Compiling Exported Programs with Torch-TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Compiling Exported Programs with Torch-TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul class="current">
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/dynamo/torch_compile.html b/docs/dynamo/torch_compile.html
index e4fb16ae75..0f0a1278c9 100644
--- a/docs/dynamo/torch_compile.html
+++ b/docs/dynamo/torch_compile.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>TensorRT Backend for torch.compile &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>TensorRT Backend for torch.compile &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -40,7 +40,7 @@
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
     <link rel="next" title="Compiling Exported Programs with Torch-TensorRT" href="dynamo_export.html" />
-    <link rel="prev" title="Refitting Torch-TensorRT Programs with New Weights" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html" />
+    <link rel="prev" title="Mutable Torch TensorRT Module" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html" />
   <!-- Google Tag Manager -->
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@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul class="current">
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -621,7 +618,7 @@ <h2>Recompilation Conditions<a class="headerlink" href="#recompilation-condition
         <a href="dynamo_export.html" class="btn btn-neutral float-right" title="Compiling Exported Programs with Torch-TensorRT" accesskey="n" rel="next">Next <img src="../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
-        <a href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html" class="btn btn-neutral" title="Refitting Torch-TensorRT Programs with New Weights" accesskey="p" rel="prev"><img src="../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
+        <a href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html" class="btn btn-neutral" title="Mutable Torch TensorRT Module" accesskey="p" rel="prev"><img src="../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
       
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diff --git a/docs/fx/getting_started_with_fx_path.html b/docs/fx/getting_started_with_fx_path.html
index b48814dd2f..2a203a7b3f 100644
--- a/docs/fx/getting_started_with_fx_path.html
+++ b/docs/fx/getting_started_with_fx_path.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Torch-TensorRT (FX Frontend) User Guide &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Torch-TensorRT (FX Frontend) User Guide &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -39,7 +39,7 @@
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     <link rel="index" title="Index" href="../genindex.html" />
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-    <link rel="next" title="Serving a Torch-TensorRT model with Triton" href="../tutorials/serving_torch_tensorrt_with_triton.html" />
+    <link rel="next" title="Compiling ResNet with dynamic shapes using the torch.compile backend" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html" />
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@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul class="current">
 <li class="toctree-l1 current"><a class="current reference internal" href="#">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -772,7 +769,7 @@ <h3>How to Add a Missing Op<a class="headerlink" href="#how-to-add-a-missing-op"
   
     <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
       
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+        <a href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html" class="btn btn-neutral float-right" title="Compiling ResNet with dynamic shapes using the torch.compile backend" accesskey="n" rel="next">Next <img src="../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
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diff --git a/docs/genindex.html b/docs/genindex.html
index 01cc73faa0..f4d6ac0ed4 100644
--- a/docs/genindex.html
+++ b/docs/genindex.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Index &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Index &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/getting_started/installation.html b/docs/getting_started/installation.html
index 8b184470c5..bec54f70e1 100644
--- a/docs/getting_started/installation.html
+++ b/docs/getting_started/installation.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Installation &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Installation &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/getting_started/quick_start.html b/docs/getting_started/quick_start.html
index c67751e4c2..8514f31d04 100644
--- a/docs/getting_started/quick_start.html
+++ b/docs/getting_started/quick_start.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Quick Start &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Quick Start &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/index.html b/docs/index.html
index 994ced60b0..e6249f82a2 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Torch-TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Torch-TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -274,7 +274,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -319,6 +319,11 @@
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -338,22 +343,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -500,7 +497,7 @@ <h2>User Guide<a class="headerlink" href="#user-guide" title="Permalink to this
 <section id="dynamo-frontend">
 <h2>Dynamo Frontend<a class="headerlink" href="#dynamo-frontend" title="Permalink to this heading">¶</a></h2>
 <ul class="simple">
-<li><p><a class="reference internal" href="tutorials/_rendered_examples/dynamo/index.html#torch-compile"><span class="std std-ref">Torch-TensorRT Examples</span></a></p></li>
+<li><p><a class="reference internal" href="dynamo/torch_compile.html#torch-compile"><span class="std std-ref">TensorRT Backend for torch.compile</span></a></p></li>
 <li><p><a class="reference internal" href="dynamo/dynamo_export.html#dynamo-export"><span class="std std-ref">Compiling Exported Programs with Torch-TensorRT</span></a></p></li>
 </ul>
 <div class="toctree-wrapper compound">
@@ -525,12 +522,15 @@ <h2>FX Frontend<a class="headerlink" href="#fx-frontend" title="Permalink to thi
 <div class="toctree-wrapper compound">
 </div>
 </section>
-<section id="tutorials">
-<h2>Tutorials<a class="headerlink" href="#tutorials" title="Permalink to this heading">¶</a></h2>
+<section id="model-zoo">
+<h2>Model Zoo<a class="headerlink" href="#model-zoo" title="Permalink to this heading">¶</a></h2>
 <ul class="simple">
-<li><p><a class="reference internal" href="tutorials/_rendered_examples/index.html#torch-tensorrt-tutorials"><span class="std std-ref">Torch-TensorRT Tutorials</span></a></p></li>
-<li><p><a class="reference internal" href="tutorials/serving_torch_tensorrt_with_triton.html#serving-torch-tensorrt-with-triton"><span class="std std-ref">Serving a Torch-TensorRT model with Triton</span></a></p></li>
-<li><p><a class="reference internal" href="tutorials/notebooks.html#notebooks"><span class="std std-ref">Example notebooks</span></a></p></li>
+<li><p><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html#torch-compile-resnet"><span class="std std-ref">Compiling ResNet with dynamic shapes using the torch.compile backend</span></a></p></li>
+<li><p><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html#torch-compile-transformer"><span class="std std-ref">Compiling BERT using the torch.compile backend</span></a></p></li>
+<li><p><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html#torch-compile-stable-diffusion"><span class="std std-ref">Compiling Stable Diffusion model using the torch.compile backend</span></a></p></li>
+<li><p><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#torch-export-gpt2"><span class="std std-ref">Compiling GPT2 using the dynamo backend</span></a></p></li>
+<li><p><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html#torch-export-llama2"><span class="std std-ref">Compiling Llama2 using the dynamo backend</span></a></p></li>
+<li><p><a class="reference internal" href="tutorials/notebooks.html#notebooks"><span class="std std-ref">Legacy notebooks</span></a></p></li>
 </ul>
 <div class="toctree-wrapper compound">
 </div>
@@ -652,7 +652,7 @@ <h2>Legacy Further Information (TorchScript)<a class="headerlink" href="#legacy-
 <li><a class="reference internal" href="#dynamo-frontend">Dynamo Frontend</a></li>
 <li><a class="reference internal" href="#torchscript-frontend">TorchScript Frontend</a></li>
 <li><a class="reference internal" href="#fx-frontend">FX Frontend</a></li>
-<li><a class="reference internal" href="#tutorials">Tutorials</a></li>
+<li><a class="reference internal" href="#model-zoo">Model Zoo</a></li>
 <li><a class="reference internal" href="#python-api-documentation">Python API Documentation</a></li>
 <li><a class="reference internal" href="#c-api-documentation">C++ API Documentation</a></li>
 <li><a class="reference internal" href="#cli-documentation">CLI Documentation</a></li>
diff --git a/docs/indices/supported_ops.html b/docs/indices/supported_ops.html
index db657622f5..24b2c14a64 100644
--- a/docs/indices/supported_ops.html
+++ b/docs/indices/supported_ops.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Operators Supported &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Operators Supported &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -274,7 +274,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -319,6 +319,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -338,22 +343,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/objects.inv b/docs/objects.inv
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diff --git a/docs/py-modindex.html b/docs/py-modindex.html
index 0e29610023..ecc4fda987 100644
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+++ b/docs/py-modindex.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Python Module Index &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Python Module Index &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
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@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/py_api/dynamo.html b/docs/py_api/dynamo.html
index 0682eed0d4..a500a106f8 100644
--- a/docs/py_api/dynamo.html
+++ b/docs/py_api/dynamo.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.dynamo &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.dynamo &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul class="current">
diff --git a/docs/py_api/fx.html b/docs/py_api/fx.html
index f54f506b77..0cf2efb5e8 100644
--- a/docs/py_api/fx.html
+++ b/docs/py_api/fx.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.fx &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.fx &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul class="current">
diff --git a/docs/py_api/logging.html b/docs/py_api/logging.html
index 7a07aa9ac4..663da37cac 100644
--- a/docs/py_api/logging.html
+++ b/docs/py_api/logging.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.logging &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.logging &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul class="current">
diff --git a/docs/py_api/ptq.html b/docs/py_api/ptq.html
index 8ff6e17671..4e00bc6b5d 100644
--- a/docs/py_api/ptq.html
+++ b/docs/py_api/ptq.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.ts.ptq &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.ts.ptq &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul class="current">
diff --git a/docs/py_api/runtime.html b/docs/py_api/runtime.html
index 5841bd242e..b4ddc5469d 100644
--- a/docs/py_api/runtime.html
+++ b/docs/py_api/runtime.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.runtime &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.runtime &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul class="current">
diff --git a/docs/py_api/torch_tensorrt.html b/docs/py_api/torch_tensorrt.html
index 7ae58d2f8f..878845d188 100644
--- a/docs/py_api/torch_tensorrt.html
+++ b/docs/py_api/torch_tensorrt.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -40,7 +40,7 @@
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-    <link rel="prev" title="Compiling Llama2 using the Torch-TensorRT with dynamo backend" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html" />
+    <link rel="prev" title="Legacy notebooks" href="../tutorials/notebooks.html" />
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@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul class="current">
@@ -1512,7 +1509,7 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
         <a href="logging.html" class="btn btn-neutral float-right" title="torch_tensorrt.logging" accesskey="n" rel="next">Next <img src="../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
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+        <a href="../tutorials/notebooks.html" class="btn btn-neutral" title="Legacy notebooks" accesskey="p" rel="prev"><img src="../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
       
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diff --git a/docs/py_api/ts.html b/docs/py_api/ts.html
index ff2070b2c8..9f08d0737c 100644
--- a/docs/py_api/ts.html
+++ b/docs/py_api/ts.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>torch_tensorrt.ts &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>torch_tensorrt.ts &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul class="current">
@@ -688,7 +685,7 @@ <h2>Functions<a class="headerlink" href="#functions" title="Permalink to this he
 
 <dl class="py function">
 <dt class="sig sig-object py" id="torch_tensorrt.ts.TensorRTCompileSpec">
-<span class="sig-prename descclassname"><span class="pre">torch_tensorrt.ts.</span></span><span class="sig-name descname"><span class="pre">TensorRTCompileSpec</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">torch.Tensor</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="torch_tensorrt.html#torch_tensorrt.Input" title="torch_tensorrt._Input.Input"><span class="pre">Input</span></a><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_signature</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">device</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">torch.device</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="torch_tensorrt.html#torch_tensorrt.Device" title="torch_tensorrt._Device.Device"><span class="pre">Device</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">Device(type=DeviceType.GPU,</span> <span class="pre">gpu_id=0)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">disable_tf32</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sparse_weights</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">enabled_precisions</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Set</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">dtype</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="torch_tensorrt.html#torch_tensorrt.dtype" title="torch_tensorrt._enums.dtype"><span class="pre">dtype</span></a><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">refit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">debug</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">capability</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="torch_tensorrt.html#torch_tensorrt.EngineCapability" title="torch_tensorrt._enums.EngineCapability"><span class="pre">EngineCapability</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">EngineCapability.STANDARD</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_avg_timing_iters</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">workspace_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dla_sram_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1048576</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dla_local_dram_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1073741824</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dla_global_dram_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">536870912</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">truncate_long_and_double</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">calibrator</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">object</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">allow_shape_tensors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">&lt;torch.ScriptClass</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7fd8d41b5d30&gt;</span></span></span><a class="reference internal" href="../_modules/torch_tensorrt/ts/_compile_spec.html#TensorRTCompileSpec"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch_tensorrt.ts.TensorRTCompileSpec" title="Permalink to this definition">¶</a></dt>
+<span class="sig-prename descclassname"><span class="pre">torch_tensorrt.ts.</span></span><span class="sig-name descname"><span class="pre">TensorRTCompileSpec</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">inputs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">List</span><span class="p"><span class="pre">[</span></span><span class="pre">torch.Tensor</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="torch_tensorrt.html#torch_tensorrt.Input" title="torch_tensorrt._Input.Input"><span class="pre">Input</span></a><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">input_signature</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Any</span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">device</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">torch.device</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="torch_tensorrt.html#torch_tensorrt.Device" title="torch_tensorrt._Device.Device"><span class="pre">Device</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">Device(type=DeviceType.GPU,</span> <span class="pre">gpu_id=0)</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">disable_tf32</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sparse_weights</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">enabled_precisions</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Optional</span><span class="p"><span class="pre">[</span></span><span class="pre">Set</span><span class="p"><span class="pre">[</span></span><span class="pre">Union</span><span class="p"><span class="pre">[</span></span><span class="pre">dtype</span><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="torch_tensorrt.html#torch_tensorrt.dtype" title="torch_tensorrt._enums.dtype"><span class="pre">dtype</span></a><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span><span class="p"><span class="pre">]</span></span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">refit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">debug</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">capability</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="torch_tensorrt.html#torch_tensorrt.EngineCapability" title="torch_tensorrt._enums.EngineCapability"><span class="pre">EngineCapability</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">EngineCapability.STANDARD</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_avg_timing_iters</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">workspace_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dla_sram_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1048576</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dla_local_dram_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">1073741824</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dla_global_dram_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">int</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">536870912</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">truncate_long_and_double</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">calibrator</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">object</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">allow_shape_tensors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">bool</span></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">&#x2192;</span> <span class="sig-return-typehint"><span class="pre">&lt;torch.ScriptClass</span> <span class="pre">object</span> <span class="pre">at</span> <span class="pre">0x7f2b1f204670&gt;</span></span></span><a class="reference internal" href="../_modules/torch_tensorrt/ts/_compile_spec.html#TensorRTCompileSpec"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#torch_tensorrt.ts.TensorRTCompileSpec" title="Permalink to this definition">¶</a></dt>
 <dd><p>Utility to create a formatted spec dictionary for using the PyTorch TensorRT backend</p>
 <dl class="field-list simple">
 <dt class="field-odd">Keyword Arguments</dt>
diff --git a/docs/search.html b/docs/search.html
index eb8bec8b33..c8345c65a2 100644
--- a/docs/search.html
+++ b/docs/search.html
@@ -9,7 +9,7 @@
   
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Search &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Search &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -272,7 +272,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -317,6 +317,11 @@
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -336,22 +341,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/searchindex.js b/docs/searchindex.js
index ce54a9f02f..6b15401929 100644
--- a/docs/searchindex.js
+++ b/docs/searchindex.js
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diff --git a/docs/sg_execution_times.html b/docs/sg_execution_times.html
index e6817ab681..5f9a4eb7ad 100644
--- a/docs/sg_execution_times.html
+++ b/docs/sg_execution_times.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Computation times &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Computation times &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
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+                  v2.6.0.dev0+2c517be
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@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -494,15 +491,15 @@
 <td><p>00:00.000</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-resnet-example-py"><span class="std std-ref">Compiling ResNet using the Torch-TensorRT torch.compile Backend</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/dynamo/torch_compile_resnet_example.py</span></code>)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-resnet-example-py"><span class="std std-ref">Compiling ResNet with dynamic shapes using the torch.compile backend</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/dynamo/torch_compile_resnet_example.py</span></code>)</p></td>
 <td><p>00:00.000</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-stable-diffusion-py"><span class="std std-ref">Torch Compile Stable Diffusion</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/dynamo/torch_compile_stable_diffusion.py</span></code>)</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-stable-diffusion-py"><span class="std std-ref">Compiling Stable Diffusion model using the torch.compile backend</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/dynamo/torch_compile_stable_diffusion.py</span></code>)</p></td>
 <td><p>00:00.000</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-transformers-example-py"><span class="std std-ref">Compiling a Transformer using torch.compile and TensorRT</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/dynamo/torch_compile_transformers_example.py</span></code>)</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-transformers-example-py"><span class="std std-ref">Compiling BERT using the torch.compile backend</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/dynamo/torch_compile_transformers_example.py</span></code>)</p></td>
 <td><p>00:00.000</p></td>
 <td><p>0.0</p></td>
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diff --git a/docs/src/pytorch-sphinx-theme/docs/changelog.html b/docs/src/pytorch-sphinx-theme/docs/changelog.html
index fd9c50ca79..f6d5d05dd9 100644
--- a/docs/src/pytorch-sphinx-theme/docs/changelog.html
+++ b/docs/src/pytorch-sphinx-theme/docs/changelog.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Changelog &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Changelog &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/src/pytorch-sphinx-theme/docs/configuring.html b/docs/src/pytorch-sphinx-theme/docs/configuring.html
index 42b5f2e9e5..3c746e8165 100644
--- a/docs/src/pytorch-sphinx-theme/docs/configuring.html
+++ b/docs/src/pytorch-sphinx-theme/docs/configuring.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Configuration &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Configuration &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/src/pytorch-sphinx-theme/docs/demo/api.html b/docs/src/pytorch-sphinx-theme/docs/demo/api.html
index f45b3903d0..f76cf8e6f0 100644
--- a/docs/src/pytorch-sphinx-theme/docs/demo/api.html
+++ b/docs/src/pytorch-sphinx-theme/docs/demo/api.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>5. :mod:`test_py_module` &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>5. :mod:`test_py_module` &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/src/pytorch-sphinx-theme/docs/demo/demo.html b/docs/src/pytorch-sphinx-theme/docs/demo/demo.html
index 7c40ca358e..71ab0beae4 100644
--- a/docs/src/pytorch-sphinx-theme/docs/demo/demo.html
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@@ -12,7 +12,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>3. Paragraph Level Markup &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>3. Paragraph Level Markup &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -661,7 +658,7 @@ <h3><a class="toc-backref" href="#id41"><span class="section-number">3.4.4. </sp
 <section id="code-blocks">
 <h3><a class="toc-backref" href="#id42"><span class="section-number">3.4.5. </span>Code Blocks</a><a class="headerlink" href="#code-blocks" title="Permalink to this heading">¶</a></h3>
 <pre class="literal-block"># parsed-literal test
-curl -O <a class="reference external" href="http://someurl/release">http://someurl/release</a>-v2.6.0.dev0+743fdbd.tar-gz</pre>
+curl -O <a class="reference external" href="http://someurl/release">http://someurl/release</a>-v2.6.0.dev0+2c517be.tar-gz</pre>
 <div class="literal-block-wrapper docutils container" id="id23">
 <div class="code-block-caption"><span class="caption-text">Code Blocks can have captions.</span><a class="headerlink" href="#id23" title="Permalink to this code">¶</a></div>
 <div class="highlight-json notranslate"><div class="highlight"><pre><span></span><span class="p">{</span>
diff --git a/docs/src/pytorch-sphinx-theme/docs/demo/lists_tables.html b/docs/src/pytorch-sphinx-theme/docs/demo/lists_tables.html
index 0ec044dade..8917421495 100644
--- a/docs/src/pytorch-sphinx-theme/docs/demo/lists_tables.html
+++ b/docs/src/pytorch-sphinx-theme/docs/demo/lists_tables.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>4. Lists &amp; Tables &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>4. Lists &amp; Tables &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/src/pytorch-sphinx-theme/docs/demo/long.html b/docs/src/pytorch-sphinx-theme/docs/demo/long.html
index e39d32b46d..77a4367209 100644
--- a/docs/src/pytorch-sphinx-theme/docs/demo/long.html
+++ b/docs/src/pytorch-sphinx-theme/docs/demo/long.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>1. Long Sticky Nav &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>1. Long Sticky Nav &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/notebooks.html">Example notebooks</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
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@@ -318,6 +318,11 @@
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 <li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
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 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
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 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
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-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
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-<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../../tutorials/notebooks.html">Legacy notebooks</a></li>
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@@ -273,7 +273,7 @@
               
               
                 <div class="version">
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@@ -318,6 +318,11 @@
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 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
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 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
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-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
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 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
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diff --git a/docs/src/pytorch-sphinx-theme/docs/installing.html b/docs/src/pytorch-sphinx-theme/docs/installing.html
index 79def48514..2c72f05b47 100644
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@@ -10,7 +10,7 @@
 
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-  <title>Installation &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Installation &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
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@@ -318,6 +318,11 @@
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 <li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
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 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
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 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
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-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
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-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
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+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/ts/creating_torchscript_module_in_python.html b/docs/ts/creating_torchscript_module_in_python.html
index be8b9db988..dc6378b57c 100644
--- a/docs/ts/creating_torchscript_module_in_python.html
+++ b/docs/ts/creating_torchscript_module_in_python.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Creating a TorchScript Module &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Creating a TorchScript Module &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/ts/getting_started_with_cpp_api.html b/docs/ts/getting_started_with_cpp_api.html
index 61e50a087f..70a79ebcec 100644
--- a/docs/ts/getting_started_with_cpp_api.html
+++ b/docs/ts/getting_started_with_cpp_api.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Using Torch-TensorRT in C++ &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Using Torch-TensorRT in C++ &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/ts/getting_started_with_python_api.html b/docs/ts/getting_started_with_python_api.html
index 2049d601e8..82953e7526 100644
--- a/docs/ts/getting_started_with_python_api.html
+++ b/docs/ts/getting_started_with_python_api.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Using Torch-TensorRT in Python &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Using Torch-TensorRT in Python &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/ts/ptq.html b/docs/ts/ptq.html
index 5b7fdc0b41..f13cf77e3f 100644
--- a/docs/ts/ptq.html
+++ b/docs/ts/ptq.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Post Training Quantization (PTQ) &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Post Training Quantization (PTQ) &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/ts/torchscript_frontend_from_pytorch.html b/docs/ts/torchscript_frontend_from_pytorch.html
index 9764b12baf..80b7d47aa8 100644
--- a/docs/ts/torchscript_frontend_from_pytorch.html
+++ b/docs/ts/torchscript_frontend_from_pytorch.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Using Torch-TensorRT TorchScript Frontend Directly From PyTorch &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Using Torch-TensorRT TorchScript Frontend Directly From PyTorch &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/tutorials/_rendered_examples/dynamo/converter_overloading.html b/docs/tutorials/_rendered_examples/dynamo/converter_overloading.html
index 8268dfe063..bbbda4b1c7 100644
--- a/docs/tutorials/_rendered_examples/dynamo/converter_overloading.html
+++ b/docs/tutorials/_rendered_examples/dynamo/converter_overloading.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Overloading Torch-TensorRT Converters with Custom Converters &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Overloading Torch-TensorRT Converters with Custom Converters &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -309,7 +309,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../getting_started/quick_start.html">Quick Start</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">User Guide</span></p>
-<ul>
+<ul class="current">
 <li class="toctree-l1"><a class="reference internal" href="../../../user_guide/torch_tensorrt_explained.html">Torch-TensorRT Explained</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../user_guide/dynamic_shapes.html">Dynamic shapes with Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../user_guide/saving_models.html">Saving models compiled with Torch-TensorRT</a></li>
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
-<ul class="current">
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1 current"><a class="current reference internal" href="#">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html b/docs/tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html
index ac1d85f43b..aa9b8645d0 100644
--- a/docs/tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html
+++ b/docs/tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Using Custom Kernels within TensorRT Engines with Torch-TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Using Custom Kernels within TensorRT Engines with Torch-TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -309,7 +309,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../getting_started/quick_start.html">Quick Start</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">User Guide</span></p>
-<ul>
+<ul class="current">
 <li class="toctree-l1"><a class="reference internal" href="../../../user_guide/torch_tensorrt_explained.html">Torch-TensorRT Explained</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../user_guide/dynamic_shapes.html">Dynamic shapes with Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../user_guide/saving_models.html">Saving models compiled with Torch-TensorRT</a></li>
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
-<ul class="current">
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1 current"><a class="current reference internal" href="#">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/tutorials/_rendered_examples/dynamo/engine_caching_bert_example.html b/docs/tutorials/_rendered_examples/dynamo/engine_caching_bert_example.html
index 101db41ebf..4c17323b9e 100644
--- a/docs/tutorials/_rendered_examples/dynamo/engine_caching_bert_example.html
+++ b/docs/tutorials/_rendered_examples/dynamo/engine_caching_bert_example.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Engine Caching (BERT) &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Engine Caching (BERT) &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/tutorials/_rendered_examples/dynamo/engine_caching_example.html b/docs/tutorials/_rendered_examples/dynamo/engine_caching_example.html
index 1372df424e..9077257356 100644
--- a/docs/tutorials/_rendered_examples/dynamo/engine_caching_example.html
+++ b/docs/tutorials/_rendered_examples/dynamo/engine_caching_example.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Engine Caching &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Engine Caching &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1 current"><a class="current reference internal" href="#">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/tutorials/_rendered_examples/dynamo/index.html b/docs/tutorials/_rendered_examples/dynamo/index.html
index cbc7034115..5af86dcdc3 100644
--- a/docs/tutorials/_rendered_examples/dynamo/index.html
+++ b/docs/tutorials/_rendered_examples/dynamo/index.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Torch-TensorRT Examples &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Dependencies &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -426,7 +423,7 @@
       </li>
 
         
-      <li>Torch-TensorRT Examples</li>
+      <li>Dependencies</li>
     
     
       <li class="pytorch-breadcrumbs-aside">
@@ -462,43 +459,26 @@
             <div role="main" class="main-content" itemscope="itemscope" itemtype="http://schema.org/Article">
              <article itemprop="articleBody" id="pytorch-article" class="pytorch-article">
               
-  <section id="torch-tensorrt-examples">
-<span id="torch-compile"></span><span id="sphx-glr-tutorials-rendered-examples-dynamo"></span><h1>Torch-TensorRT Examples<a class="headerlink" href="#torch-tensorrt-examples" title="Permalink to this heading">¶</a></h1>
-<p>Please refer to the following examples which demonstrate the usage of different features of Torch-TensorRT. We also provide
-examples of Torch-TensorRT compilation of select computer vision and language models.</p>
+  <p id="torch-tensorrt-examples"><span id="sphx-glr-tutorials-rendered-examples-dynamo"></span>Here we provide examples of Torch-TensorRT compilation of popular computer vision and language models.</p>
 <section id="dependencies">
-<h2>Dependencies<a class="headerlink" href="#dependencies" title="Permalink to this heading">¶</a></h2>
+<h1>Dependencies<a class="headerlink" href="#dependencies" title="Permalink to this heading">¶</a></h1>
 <p>Please install the following external dependencies (assuming you already have correct <cite>torch</cite>, <cite>torch_tensorrt</cite> and <cite>tensorrt</cite> libraries installed (<a class="reference external" href="https://github.com/pytorch/TensorRT?tab=readme-ov-file#dependencies">dependencies</a>))</p>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">pip</span> <span class="n">install</span> <span class="o">-</span><span class="n">r</span> <span class="n">requirements</span><span class="o">.</span><span class="n">txt</span>
 </pre></div>
 </div>
 </section>
-<section id="compiler-features">
-<h2>Compiler Features<a class="headerlink" href="#compiler-features" title="Permalink to this heading">¶</a></h2>
-<ul class="simple">
-<li><p><a class="reference internal" href="torch_compile_advanced_usage.html#torch-compile-advanced-usage"><span class="std std-ref">Torch Compile Advanced Usage</span></a>: Advanced usage including making a custom backend to use directly with the <code class="docutils literal notranslate"><span class="pre">torch.compile</span></code> API</p></li>
-<li><p><a class="reference internal" href="torch_export_cudagraphs.html#torch-export-cudagraphs"><span class="std std-ref">Torch Export with Cudagraphs</span></a>: Using the Cudagraphs integration with <cite>ir=”dynamo”</cite></p></li>
-<li><p><a class="reference internal" href="converter_overloading.html#converter-overloading"><span class="std std-ref">Overloading Torch-TensorRT Converters with Custom Converters</span></a>: How to write custom converters and overload existing ones</p></li>
-<li><p><a class="reference internal" href="custom_kernel_plugins.html#custom-kernel-plugins"><span class="std std-ref">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</span></a>: Creating a plugin to use a custom kernel inside TensorRT engines</p></li>
-<li><p><a class="reference internal" href="refit_engine_example.html#refit-engine-example"><span class="std std-ref">Refitting Torch-TensorRT Programs with New Weights</span></a>: Refitting a compiled TensorRT Graph Module with updated weights</p></li>
-<li><p><a class="reference internal" href="mutable_torchtrt_module_example.html#mutable-torchtrt-module-example"><span class="std std-ref">Mutable Torch TensorRT Module</span></a>: Compile, use, and modify TensorRT Graph Module with MutableTorchTensorRTModule</p></li>
-<li><p><span class="xref std std-ref">vgg16_fp8_ptq</span>: Compiling a VGG16 model with FP8 and PTQ using <code class="docutils literal notranslate"><span class="pre">torch.compile</span></code></p></li>
-<li><p><a class="reference internal" href="engine_caching_example.html#engine-caching-example"><span class="std std-ref">Engine Caching</span></a>: Utilizing engine caching to speed up compilation times</p></li>
-<li><p><a class="reference internal" href="engine_caching_bert_example.html#engine-caching-bert-example"><span class="std std-ref">Engine Caching (BERT)</span></a>: Demonstrating engine caching on BERT</p></li>
-</ul>
-</section>
 <section id="model-zoo">
-<h2>Model Zoo<a class="headerlink" href="#model-zoo" title="Permalink to this heading">¶</a></h2>
+<h1>Model Zoo<a class="headerlink" href="#model-zoo" title="Permalink to this heading">¶</a></h1>
 <ul class="simple">
-<li><p><a class="reference internal" href="torch_compile_resnet_example.html#torch-compile-resnet"><span class="std std-ref">Compiling ResNet using the Torch-TensorRT torch.compile Backend</span></a>: Compiling a ResNet model using the Torch Compile Frontend for <code class="docutils literal notranslate"><span class="pre">torch_tensorrt.compile</span></code></p></li>
-<li><p><a class="reference internal" href="torch_compile_transformers_example.html#torch-compile-transformer"><span class="std std-ref">Compiling a Transformer using torch.compile and TensorRT</span></a>: Compiling a Transformer model using <code class="docutils literal notranslate"><span class="pre">torch.compile</span></code></p></li>
-<li><p><a class="reference internal" href="torch_compile_stable_diffusion.html#torch-compile-stable-diffusion"><span class="std std-ref">Torch Compile Stable Diffusion</span></a>: Compiling a Stable Diffusion model using <code class="docutils literal notranslate"><span class="pre">torch.compile</span></code></p></li>
+<li><p><a class="reference internal" href="torch_compile_resnet_example.html#torch-compile-resnet"><span class="std std-ref">Compiling ResNet with dynamic shapes using the torch.compile backend</span></a>: Compiling a ResNet model using the Torch Compile Frontend for <code class="docutils literal notranslate"><span class="pre">torch_tensorrt.compile</span></code></p></li>
+<li><p><a class="reference internal" href="torch_compile_transformers_example.html#torch-compile-transformer"><span class="std std-ref">Compiling BERT using the torch.compile backend</span></a>: Compiling a Transformer model using <code class="docutils literal notranslate"><span class="pre">torch.compile</span></code></p></li>
+<li><p><a class="reference internal" href="torch_compile_stable_diffusion.html#torch-compile-stable-diffusion"><span class="std std-ref">Compiling Stable Diffusion model using the torch.compile backend</span></a>: Compiling a Stable Diffusion model using <code class="docutils literal notranslate"><span class="pre">torch.compile</span></code></p></li>
 <li><p><span class="xref std std-ref">_torch_export_gpt2</span>: Compiling a GPT2 model using AOT workflow (<cite>ir=dynamo</cite>)</p></li>
 <li><p><span class="xref std std-ref">_torch_export_llama2</span>: Compiling a Llama2 model using AOT workflow (<cite>ir=dynamo</cite>)</p></li>
 </ul>
 <div class="sphx-glr-thumbnails"><div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with torch.compi..."><img alt="" src="../../../_images/sphx_glr_torch_compile_stable_diffusion_thumb.png" />
-<p><a class="reference internal" href="torch_compile_stable_diffusion.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-stable-diffusion-py"><span class="std std-ref">Torch Compile Stable Diffusion</span></a></p>
-  <div class="sphx-glr-thumbnail-title">Torch Compile Stable Diffusion</div>
+<p><a class="reference internal" href="torch_compile_stable_diffusion.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-stable-diffusion-py"><span class="std std-ref">Compiling Stable Diffusion model using the torch.compile backend</span></a></p>
+  <div class="sphx-glr-thumbnail-title">Compiling Stable Diffusion model using the torch.compile backend</div>
 </div><div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as an overview of the process by which the Torch-TensorRT C..."><img alt="" src="../../../_images/sphx_glr_torch_export_cudagraphs_thumb.png" />
 <p><a class="reference internal" href="torch_export_cudagraphs.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-export-cudagraphs-py"><span class="std std-ref">Torch Export with Cudagraphs</span></a></p>
   <div class="sphx-glr-thumbnail-title">Torch Export with Cudagraphs</div>
@@ -506,26 +486,26 @@ <h2>Model Zoo<a class="headerlink" href="#model-zoo" title="Permalink to this he
 <p><a class="reference internal" href="refit_engine_example.html#sphx-glr-tutorials-rendered-examples-dynamo-refit-engine-example-py"><span class="std std-ref">Refitting Torch-TensorRT Programs with New Weights</span></a></p>
   <div class="sphx-glr-thumbnail-title">Refitting Torch-TensorRT Programs with New Weights</div>
 </div><div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with torch.compi..."><img alt="" src="../../../_images/sphx_glr_torch_compile_transformers_example_thumb.png" />
-<p><a class="reference internal" href="torch_compile_transformers_example.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-transformers-example-py"><span class="std std-ref">Compiling a Transformer using torch.compile and TensorRT</span></a></p>
-  <div class="sphx-glr-thumbnail-title">Compiling a Transformer using torch.compile and TensorRT</div>
+<p><a class="reference internal" href="torch_compile_transformers_example.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-transformers-example-py"><span class="std std-ref">Compiling BERT using the torch.compile backend</span></a></p>
+  <div class="sphx-glr-thumbnail-title">Compiling BERT using the torch.compile backend</div>
 </div><div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as an overview of the process by which torch_tensorrt.compi..."><img alt="" src="../../../_images/sphx_glr_torch_compile_advanced_usage_thumb.png" />
 <p><a class="reference internal" href="torch_compile_advanced_usage.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-advanced-usage-py"><span class="std std-ref">Torch Compile Advanced Usage</span></a></p>
   <div class="sphx-glr-thumbnail-title">Torch Compile Advanced Usage</div>
 </div><div class="sphx-glr-thumbcontainer" tooltip="Small caching example on BERT."><img alt="" src="../../../_images/sphx_glr_engine_caching_bert_example_thumb.png" />
 <p><a class="reference internal" href="engine_caching_bert_example.html#sphx-glr-tutorials-rendered-examples-dynamo-engine-caching-bert-example-py"><span class="std std-ref">Engine Caching (BERT)</span></a></p>
   <div class="sphx-glr-thumbnail-title">Engine Caching (BERT)</div>
-</div><div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo back..."><img alt="" src="../../../_images/sphx_glr_torch_export_llama2_thumb.png" />
-<p><a class="reference internal" href="torch_export_llama2.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-export-llama2-py"><span class="std std-ref">Compiling Llama2 using the Torch-TensorRT with dynamo backend</span></a></p>
-  <div class="sphx-glr-thumbnail-title">Compiling Llama2 using the Torch-TensorRT with dynamo backend</div>
 </div><div class="sphx-glr-thumbcontainer" tooltip="We are going to demonstrate how we can easily use Mutable Torch TensorRT Module to compile, int..."><img alt="" src="../../../_images/sphx_glr_mutable_torchtrt_module_example_thumb.png" />
 <p><a class="reference internal" href="mutable_torchtrt_module_example.html#sphx-glr-tutorials-rendered-examples-dynamo-mutable-torchtrt-module-example-py"><span class="std std-ref">Mutable Torch TensorRT Module</span></a></p>
   <div class="sphx-glr-thumbnail-title">Mutable Torch TensorRT Module</div>
 </div><div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with torch.compi..."><img alt="" src="../../../_images/sphx_glr_torch_compile_resnet_example_thumb.png" />
-<p><a class="reference internal" href="torch_compile_resnet_example.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-resnet-example-py"><span class="std std-ref">Compiling ResNet using the Torch-TensorRT torch.compile Backend</span></a></p>
-  <div class="sphx-glr-thumbnail-title">Compiling ResNet using the Torch-TensorRT torch.compile Backend</div>
-</div><div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo back..."><img alt="" src="../../../_images/sphx_glr_torch_export_gpt2_thumb.png" />
-<p><a class="reference internal" href="torch_export_gpt2.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-export-gpt2-py"><span class="std std-ref">Compiling GPT2 using the Torch-TensorRT with dynamo backend</span></a></p>
-  <div class="sphx-glr-thumbnail-title">Compiling GPT2 using the Torch-TensorRT with dynamo backend</div>
+<p><a class="reference internal" href="torch_compile_resnet_example.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-resnet-example-py"><span class="std std-ref">Compiling ResNet with dynamic shapes using the torch.compile backend</span></a></p>
+  <div class="sphx-glr-thumbnail-title">Compiling ResNet with dynamic shapes using the torch.compile backend</div>
+</div><div class="sphx-glr-thumbcontainer" tooltip="This script illustrates Torch-TensorRT workflow with dynamo backend on popular GPT2 model."><img alt="" src="../../../_images/sphx_glr_torch_export_gpt2_thumb.png" />
+<p><a class="reference internal" href="torch_export_gpt2.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-export-gpt2-py"><span class="std std-ref">Compiling GPT2 using the dynamo backend</span></a></p>
+  <div class="sphx-glr-thumbnail-title">Compiling GPT2 using the dynamo backend</div>
+</div><div class="sphx-glr-thumbcontainer" tooltip="This script illustrates Torch-TensorRT workflow with dynamo backend on popular Llama2 model."><img alt="" src="../../../_images/sphx_glr_torch_export_llama2_thumb.png" />
+<p><a class="reference internal" href="torch_export_llama2.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-export-llama2-py"><span class="std std-ref">Compiling Llama2 using the dynamo backend</span></a></p>
+  <div class="sphx-glr-thumbnail-title">Compiling Llama2 using the dynamo backend</div>
 </div><div class="sphx-glr-thumbcontainer" tooltip="If for some reason you want to change the conversion behavior of a specific PyTorch operation t..."><img alt="" src="../../../_images/sphx_glr_converter_overloading_thumb.png" />
 <p><a class="reference internal" href="converter_overloading.html#sphx-glr-tutorials-rendered-examples-dynamo-converter-overloading-py"><span class="std std-ref">Overloading Torch-TensorRT Converters with Custom Converters</span></a></p>
   <div class="sphx-glr-thumbnail-title">Overloading Torch-TensorRT Converters with Custom Converters</div>
@@ -540,7 +520,6 @@ <h2>Model Zoo<a class="headerlink" href="#model-zoo" title="Permalink to this he
   <div class="sphx-glr-thumbnail-title">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</div>
 </div></div><div class="toctree-wrapper compound">
 </div>
-</section>
 </section>
 
 
@@ -577,12 +556,8 @@ <h2>Model Zoo<a class="headerlink" href="#model-zoo" title="Permalink to this he
           <div class="pytorch-right-menu" id="pytorch-right-menu">
             <div class="pytorch-side-scroll" id="pytorch-side-scroll-right">
               <ul>
-<li><a class="reference internal" href="#">Torch-TensorRT Examples</a><ul>
-<li><a class="reference internal" href="#dependencies">Dependencies</a></li>
-<li><a class="reference internal" href="#compiler-features">Compiler Features</a></li>
+<li><a class="reference internal" href="#">Dependencies</a></li>
 <li><a class="reference internal" href="#model-zoo">Model Zoo</a></li>
-</ul>
-</li>
 </ul>
 
             </div>
diff --git a/docs/tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html b/docs/tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html
index dc9a86cfd2..222465d20f 100644
--- a/docs/tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html
+++ b/docs/tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Mutable Torch TensorRT Module &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Mutable Torch TensorRT Module &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -39,7 +39,7 @@
   <link rel="stylesheet" href="../../../_static/css/custom.css" type="text/css" />
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" />
-    <link rel="next" title="Compiling GPT2 using the Torch-TensorRT with dynamo backend" href="torch_export_gpt2.html" />
+    <link rel="next" title="TensorRT Backend for torch.compile" href="../../../dynamo/torch_compile.html" />
     <link rel="prev" title="Using Custom Kernels within TensorRT Engines with Torch-TensorRT" href="custom_kernel_plugins.html" />
   <!-- Google Tag Manager -->
     <script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -309,7 +309,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../getting_started/quick_start.html">Quick Start</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">User Guide</span></p>
-<ul>
+<ul class="current">
 <li class="toctree-l1"><a class="reference internal" href="../../../user_guide/torch_tensorrt_explained.html">Torch-TensorRT Explained</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../user_guide/dynamic_shapes.html">Dynamic shapes with Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../user_guide/saving_models.html">Saving models compiled with Torch-TensorRT</a></li>
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
-<ul class="current">
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1 current"><a class="current reference internal" href="#">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -598,7 +595,7 @@ <h2>Stable Diffusion with Huggingface<a class="headerlink" href="#stable-diffusi
   
     <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
       
-        <a href="torch_export_gpt2.html" class="btn btn-neutral float-right" title="Compiling GPT2 using the Torch-TensorRT with dynamo backend" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
+        <a href="../../../dynamo/torch_compile.html" class="btn btn-neutral float-right" title="TensorRT Backend for torch.compile" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
         <a href="custom_kernel_plugins.html" class="btn btn-neutral" title="Using Custom Kernels within TensorRT Engines with Torch-TensorRT" accesskey="p" rel="prev"><img src="../../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
diff --git a/docs/tutorials/_rendered_examples/dynamo/refit_engine_example.html b/docs/tutorials/_rendered_examples/dynamo/refit_engine_example.html
index 8325c93020..8e84e2515a 100644
--- a/docs/tutorials/_rendered_examples/dynamo/refit_engine_example.html
+++ b/docs/tutorials/_rendered_examples/dynamo/refit_engine_example.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Refitting Torch-TensorRT Programs with New Weights &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Refitting Torch-TensorRT Programs with New Weights &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -39,7 +39,7 @@
   <link rel="stylesheet" href="../../../_static/css/custom.css" type="text/css" />
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" />
-    <link rel="next" title="TensorRT Backend for torch.compile" href="../../../dynamo/torch_compile.html" />
+    <link rel="next" title="Serving a Torch-TensorRT model with Triton" href="../../serving_torch_tensorrt_with_triton.html" />
     <link rel="prev" title="Engine Caching" href="engine_caching_example.html" />
   <!-- Google Tag Manager -->
     <script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1 current"><a class="current reference internal" href="#">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -613,7 +610,7 @@ <h3>In-Place Refit<a class="headerlink" href="#in-place-refit" title="Permalink
   
     <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
       
-        <a href="../../../dynamo/torch_compile.html" class="btn btn-neutral float-right" title="TensorRT Backend for torch.compile" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
+        <a href="../../serving_torch_tensorrt_with_triton.html" class="btn btn-neutral float-right" title="Serving a Torch-TensorRT model with Triton" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
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diff --git a/docs/tutorials/_rendered_examples/dynamo/torch_compile_advanced_usage.html b/docs/tutorials/_rendered_examples/dynamo/torch_compile_advanced_usage.html
index 85a19e1ca0..b3d958c013 100644
--- a/docs/tutorials/_rendered_examples/dynamo/torch_compile_advanced_usage.html
+++ b/docs/tutorials/_rendered_examples/dynamo/torch_compile_advanced_usage.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Torch Compile Advanced Usage &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Torch Compile Advanced Usage &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html b/docs/tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html
index e8cea1e7da..d1dcc8d173 100644
--- a/docs/tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html
+++ b/docs/tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Compiling ResNet using the Torch-TensorRT torch.compile Backend &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Compiling ResNet with dynamic shapes using the torch.compile backend &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -39,8 +39,8 @@
   <link rel="stylesheet" href="../../../_static/css/custom.css" type="text/css" />
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" />
-    <link rel="next" title="Compiling a Transformer using torch.compile and TensorRT" href="torch_compile_transformers_example.html" />
-    <link rel="prev" title="Example notebooks" href="../../notebooks.html" />
+    <link rel="next" title="Compiling BERT using the torch.compile backend" href="torch_compile_transformers_example.html" />
+    <link rel="prev" title="Torch-TensorRT (FX Frontend) User Guide" href="../../../fx/getting_started_with_fx_path.html" />
   <!-- Google Tag Manager -->
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@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul class="current">
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1 current"><a class="current reference internal" href="#">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -428,7 +425,7 @@
       </li>
 
         
-      <li>Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</li>
+      <li>Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</li>
     
     
       <li class="pytorch-breadcrumbs-aside">
@@ -469,8 +466,8 @@
 <p><a class="reference internal" href="#sphx-glr-download-tutorials-rendered-examples-dynamo-torch-compile-resnet-example-py"><span class="std std-ref">Go to the end</span></a>
 to download the full example code</p>
 </div>
-<section class="sphx-glr-example-title" id="compiling-resnet-using-the-torch-tensorrt-torch-compile-backend">
-<span id="torch-compile-resnet"></span><span id="sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-resnet-example-py"></span><h1>Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend<a class="headerlink" href="#compiling-resnet-using-the-torch-tensorrt-torch-compile-backend" title="Permalink to this heading">¶</a></h1>
+<section class="sphx-glr-example-title" id="compiling-resnet-with-dynamic-shapes-using-the-torch-compile-backend">
+<span id="torch-compile-resnet"></span><span id="sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-resnet-example-py"></span><h1>Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend<a class="headerlink" href="#compiling-resnet-with-dynamic-shapes-using-the-torch-compile-backend" title="Permalink to this heading">¶</a></h1>
 <p>This interactive script is intended as a sample of the Torch-TensorRT workflow with <cite>torch.compile</cite> on a ResNet model.</p>
 <section id="imports-and-model-definition">
 <h2>Imports and Model Definition<a class="headerlink" href="#imports-and-model-definition" title="Permalink to this heading">¶</a></h2>
@@ -600,10 +597,10 @@ <h2>Avoid recompilation by specifying dynamic shapes before Torch-TRT compilatio
   
     <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
       
-        <a href="torch_compile_transformers_example.html" class="btn btn-neutral float-right" title="Compiling a Transformer using torch.compile and TensorRT" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
+        <a href="torch_compile_transformers_example.html" class="btn btn-neutral float-right" title="Compiling BERT using the torch.compile backend" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
-        <a href="../../notebooks.html" class="btn btn-neutral" title="Example notebooks" accesskey="p" rel="prev"><img src="../../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
+        <a href="../../../fx/getting_started_with_fx_path.html" class="btn btn-neutral" title="Torch-TensorRT (FX Frontend) User Guide" accesskey="p" rel="prev"><img src="../../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
       
     </div>
   
@@ -635,7 +632,7 @@ <h2>Avoid recompilation by specifying dynamic shapes before Torch-TRT compilatio
           <div class="pytorch-right-menu" id="pytorch-right-menu">
             <div class="pytorch-side-scroll" id="pytorch-side-scroll-right">
               <ul>
-<li><a class="reference internal" href="#">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a><ul>
+<li><a class="reference internal" href="#">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a><ul>
 <li><a class="reference internal" href="#imports-and-model-definition">Imports and Model Definition</a></li>
 <li><a class="reference internal" href="#optional-input-arguments-to-torch-tensorrt-compile">Optional Input Arguments to <cite>torch_tensorrt.compile</cite></a></li>
 <li><a class="reference internal" href="#compilation-with-torch-tensorrt-compile">Compilation with <cite>torch_tensorrt.compile</cite></a></li>
diff --git a/docs/tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html b/docs/tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html
index b346013ee2..fdf8803d47 100644
--- a/docs/tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html
+++ b/docs/tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Torch Compile Stable Diffusion &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Compiling Stable Diffusion model using the torch.compile backend &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -39,8 +39,8 @@
   <link rel="stylesheet" href="../../../_static/css/custom.css" type="text/css" />
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" />
-    <link rel="next" title="Torch Export with Cudagraphs" href="torch_export_cudagraphs.html" />
-    <link rel="prev" title="Compiling a Transformer using torch.compile and TensorRT" href="torch_compile_transformers_example.html" />
+    <link rel="next" title="Compiling GPT2 using the dynamo backend" href="torch_export_gpt2.html" />
+    <link rel="prev" title="Compiling BERT using the torch.compile backend" href="torch_compile_transformers_example.html" />
   <!-- Google Tag Manager -->
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     new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul class="current">
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1 current"><a class="current reference internal" href="#">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -428,7 +425,7 @@
       </li>
 
         
-      <li>Torch Compile Stable Diffusion</li>
+      <li>Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</li>
     
     
       <li class="pytorch-breadcrumbs-aside">
@@ -469,8 +466,8 @@
 <p><a class="reference internal" href="#sphx-glr-download-tutorials-rendered-examples-dynamo-torch-compile-stable-diffusion-py"><span class="std std-ref">Go to the end</span></a>
 to download the full example code</p>
 </div>
-<section class="sphx-glr-example-title" id="torch-compile-stable-diffusion">
-<span id="sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-stable-diffusion-py"></span><span id="id1"></span><h1>Torch Compile Stable Diffusion<a class="headerlink" href="#torch-compile-stable-diffusion" title="Permalink to this heading">¶</a></h1>
+<section class="sphx-glr-example-title" id="compiling-stable-diffusion-model-using-the-torch-compile-backend">
+<span id="torch-compile-stable-diffusion"></span><span id="sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-stable-diffusion-py"></span><h1>Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend<a class="headerlink" href="#compiling-stable-diffusion-model-using-the-torch-compile-backend" title="Permalink to this heading">¶</a></h1>
 <p>This interactive script is intended as a sample of the Torch-TensorRT workflow with <cite>torch.compile</cite> on a Stable Diffusion model. A sample output is featured below:</p>
 <a class="reference internal image-reference" href="../../../_images/majestic_castle.png"><img alt="../../../_images/majestic_castle.png" class="align-right" src="../../../_images/majestic_castle.png" style="width: 256.0px; height: 256.0px;" /></a>
 <section id="imports-and-model-definition">
@@ -533,10 +530,10 @@ <h2>Inference<a class="headerlink" href="#inference" title="Permalink to this he
   
     <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
       
-        <a href="torch_export_cudagraphs.html" class="btn btn-neutral float-right" title="Torch Export with Cudagraphs" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
+        <a href="torch_export_gpt2.html" class="btn btn-neutral float-right" title="Compiling GPT2 using the dynamo backend" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
-        <a href="torch_compile_transformers_example.html" class="btn btn-neutral" title="Compiling a Transformer using torch.compile and TensorRT" accesskey="p" rel="prev"><img src="../../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
+        <a href="torch_compile_transformers_example.html" class="btn btn-neutral" title="Compiling BERT using the torch.compile backend" accesskey="p" rel="prev"><img src="../../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
       
     </div>
   
@@ -568,7 +565,7 @@ <h2>Inference<a class="headerlink" href="#inference" title="Permalink to this he
           <div class="pytorch-right-menu" id="pytorch-right-menu">
             <div class="pytorch-side-scroll" id="pytorch-side-scroll-right">
               <ul>
-<li><a class="reference internal" href="#">Torch Compile Stable Diffusion</a><ul>
+<li><a class="reference internal" href="#">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a><ul>
 <li><a class="reference internal" href="#imports-and-model-definition">Imports and Model Definition</a></li>
 <li><a class="reference internal" href="#inference">Inference</a></li>
 </ul>
diff --git a/docs/tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html b/docs/tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html
index 8c41111545..49b4a4598d 100644
--- a/docs/tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html
+++ b/docs/tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Compiling a Transformer using torch.compile and TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Compiling BERT using the torch.compile backend &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -39,8 +39,8 @@
   <link rel="stylesheet" href="../../../_static/css/custom.css" type="text/css" />
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" />
-    <link rel="next" title="Torch Compile Stable Diffusion" href="torch_compile_stable_diffusion.html" />
-    <link rel="prev" title="Compiling ResNet using the Torch-TensorRT torch.compile Backend" href="torch_compile_resnet_example.html" />
+    <link rel="next" title="Compiling Stable Diffusion model using the torch.compile backend" href="torch_compile_stable_diffusion.html" />
+    <link rel="prev" title="Compiling ResNet with dynamic shapes using the torch.compile backend" href="torch_compile_resnet_example.html" />
   <!-- Google Tag Manager -->
     <script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':
     new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul class="current">
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1 current"><a class="current reference internal" href="#">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -428,7 +425,7 @@
       </li>
 
         
-      <li>Compiling a Transformer using torch.compile and TensorRT</li>
+      <li>Compiling BERT using the <cite>torch.compile</cite> backend</li>
     
     
       <li class="pytorch-breadcrumbs-aside">
@@ -469,9 +466,9 @@
 <p><a class="reference internal" href="#sphx-glr-download-tutorials-rendered-examples-dynamo-torch-compile-transformers-example-py"><span class="std std-ref">Go to the end</span></a>
 to download the full example code</p>
 </div>
-<section class="sphx-glr-example-title" id="compiling-a-transformer-using-torch-compile-and-tensorrt">
-<span id="torch-compile-transformer"></span><span id="sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-transformers-example-py"></span><h1>Compiling a Transformer using torch.compile and TensorRT<a class="headerlink" href="#compiling-a-transformer-using-torch-compile-and-tensorrt" title="Permalink to this heading">¶</a></h1>
-<p>This interactive script is intended as a sample of the Torch-TensorRT workflow with <cite>torch.compile</cite> on a transformer-based model.</p>
+<section class="sphx-glr-example-title" id="compiling-bert-using-the-torch-compile-backend">
+<span id="torch-compile-transformer"></span><span id="sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-transformers-example-py"></span><h1>Compiling BERT using the <cite>torch.compile</cite> backend<a class="headerlink" href="#compiling-bert-using-the-torch-compile-backend" title="Permalink to this heading">¶</a></h1>
+<p>This interactive script is intended as a sample of the Torch-TensorRT workflow with <cite>torch.compile</cite> on a BERT model.</p>
 <section id="imports-and-model-definition">
 <h2>Imports and Model Definition<a class="headerlink" href="#imports-and-model-definition" title="Permalink to this heading">¶</a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">torch</span>
@@ -588,10 +585,10 @@ <h2>Cuda Driver Error Note<a class="headerlink" href="#cuda-driver-error-note" t
   
     <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
       
-        <a href="torch_compile_stable_diffusion.html" class="btn btn-neutral float-right" title="Torch Compile Stable Diffusion" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
+        <a href="torch_compile_stable_diffusion.html" class="btn btn-neutral float-right" title="Compiling Stable Diffusion model using the torch.compile backend" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
-        <a href="torch_compile_resnet_example.html" class="btn btn-neutral" title="Compiling ResNet using the Torch-TensorRT torch.compile Backend" accesskey="p" rel="prev"><img src="../../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
+        <a href="torch_compile_resnet_example.html" class="btn btn-neutral" title="Compiling ResNet with dynamic shapes using the torch.compile backend" accesskey="p" rel="prev"><img src="../../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
       
     </div>
   
@@ -623,7 +620,7 @@ <h2>Cuda Driver Error Note<a class="headerlink" href="#cuda-driver-error-note" t
           <div class="pytorch-right-menu" id="pytorch-right-menu">
             <div class="pytorch-side-scroll" id="pytorch-side-scroll-right">
               <ul>
-<li><a class="reference internal" href="#">Compiling a Transformer using torch.compile and TensorRT</a><ul>
+<li><a class="reference internal" href="#">Compiling BERT using the <cite>torch.compile</cite> backend</a><ul>
 <li><a class="reference internal" href="#imports-and-model-definition">Imports and Model Definition</a></li>
 <li><a class="reference internal" href="#optional-input-arguments-to-torch-tensorrt-compile">Optional Input Arguments to <cite>torch_tensorrt.compile</cite></a></li>
 <li><a class="reference internal" href="#compilation-with-torch-compile">Compilation with <cite>torch.compile</cite></a></li>
diff --git a/docs/tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html b/docs/tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html
index 1b591b79c0..4f375eb503 100644
--- a/docs/tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html
+++ b/docs/tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Torch Export with Cudagraphs &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Torch Export with Cudagraphs &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -40,7 +40,7 @@
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" />
     <link rel="next" title="Overloading Torch-TensorRT Converters with Custom Converters" href="converter_overloading.html" />
-    <link rel="prev" title="Torch Compile Stable Diffusion" href="torch_compile_stable_diffusion.html" />
+    <link rel="prev" title="Serving a Torch-TensorRT model with Triton" href="../../serving_torch_tensorrt_with_triton.html" />
   <!-- Google Tag Manager -->
     <script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':
     new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -309,7 +309,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../../../getting_started/quick_start.html">Quick Start</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">User Guide</span></p>
-<ul>
+<ul class="current">
 <li class="toctree-l1"><a class="reference internal" href="../../../user_guide/torch_tensorrt_explained.html">Torch-TensorRT Explained</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../user_guide/dynamic_shapes.html">Dynamic shapes with Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../../../user_guide/saving_models.html">Saving models compiled with Torch-TensorRT</a></li>
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
-<ul class="current">
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1 current"><a class="current reference internal" href="#">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -555,7 +552,7 @@ <h2>Inference using the Cudagraphs Integration<a class="headerlink" href="#infer
         <a href="converter_overloading.html" class="btn btn-neutral float-right" title="Overloading Torch-TensorRT Converters with Custom Converters" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
-        <a href="torch_compile_stable_diffusion.html" class="btn btn-neutral" title="Torch Compile Stable Diffusion" accesskey="p" rel="prev"><img src="../../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
+        <a href="../../serving_torch_tensorrt_with_triton.html" class="btn btn-neutral" title="Serving a Torch-TensorRT model with Triton" accesskey="p" rel="prev"><img src="../../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
       
     </div>
   
diff --git a/docs/tutorials/_rendered_examples/dynamo/torch_export_gpt2.html b/docs/tutorials/_rendered_examples/dynamo/torch_export_gpt2.html
index 8418aa7e30..2c297df9bd 100644
--- a/docs/tutorials/_rendered_examples/dynamo/torch_export_gpt2.html
+++ b/docs/tutorials/_rendered_examples/dynamo/torch_export_gpt2.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Compiling GPT2 using the Torch-TensorRT with dynamo backend &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Compiling GPT2 using the dynamo backend &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -39,8 +39,8 @@
   <link rel="stylesheet" href="../../../_static/css/custom.css" type="text/css" />
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" />
-    <link rel="next" title="Compiling Llama2 using the Torch-TensorRT with dynamo backend" href="torch_export_llama2.html" />
-    <link rel="prev" title="Mutable Torch TensorRT Module" href="mutable_torchtrt_module_example.html" />
+    <link rel="next" title="Compiling Llama2 using the dynamo backend" href="torch_export_llama2.html" />
+    <link rel="prev" title="Compiling Stable Diffusion model using the torch.compile backend" href="torch_compile_stable_diffusion.html" />
   <!-- Google Tag Manager -->
     <script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':
     new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul class="current">
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1 current"><a class="current reference internal" href="#">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -428,7 +425,7 @@
       </li>
 
         
-      <li>Compiling GPT2 using the Torch-TensorRT with dynamo backend</li>
+      <li>Compiling GPT2 using the dynamo backend</li>
     
     
       <li class="pytorch-breadcrumbs-aside">
@@ -469,9 +466,9 @@
 <p><a class="reference internal" href="#sphx-glr-download-tutorials-rendered-examples-dynamo-torch-export-gpt2-py"><span class="std std-ref">Go to the end</span></a>
 to download the full example code</p>
 </div>
-<section class="sphx-glr-example-title" id="compiling-gpt2-using-the-torch-tensorrt-with-dynamo-backend">
-<span id="torch-export-gpt2"></span><span id="sphx-glr-tutorials-rendered-examples-dynamo-torch-export-gpt2-py"></span><h1>Compiling GPT2 using the Torch-TensorRT with dynamo backend<a class="headerlink" href="#compiling-gpt2-using-the-torch-tensorrt-with-dynamo-backend" title="Permalink to this heading">¶</a></h1>
-<p>This interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo backend on a GPT2 model.</p>
+<section class="sphx-glr-example-title" id="compiling-gpt2-using-the-dynamo-backend">
+<span id="torch-export-gpt2"></span><span id="sphx-glr-tutorials-rendered-examples-dynamo-torch-export-gpt2-py"></span><h1>Compiling GPT2 using the dynamo backend<a class="headerlink" href="#compiling-gpt2-using-the-dynamo-backend" title="Permalink to this heading">¶</a></h1>
+<p>This script illustrates Torch-TensorRT workflow with dynamo backend on popular GPT2 model.</p>
 <section id="imports-and-model-definition">
 <h2>Imports and Model Definition<a class="headerlink" href="#imports-and-model-definition" title="Permalink to this heading">¶</a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">torch</span>
@@ -551,18 +548,14 @@ <h2>Decode the output sentences of PyTorch and TensorRT<a class="headerlink" hre
     <span class="s2">&quot;TensorRT model generated text: &quot;</span><span class="p">,</span>
     <span class="n">tokenizer</span><span class="o">.</span><span class="n">decode</span><span class="p">(</span><span class="n">trt_gen_tokens</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">skip_special_tokens</span><span class="o">=</span><span class="kc">True</span><span class="p">),</span>
 <span class="p">)</span>
-</pre></div>
-</div>
-</section>
-</section>
-<section id="the-output-sentences-should-look-like">
-<h1>The output sentences should look like<a class="headerlink" href="#the-output-sentences-should-look-like" title="Permalink to this heading">¶</a></h1>
-<p>Pytorch model generated text:  What is parallel programming ?</p>
-<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="c1"># The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that</span>
+
+<span class="c1"># Prompt : What is parallel programming ?</span>
+
 <span class="c1"># =============================</span>
-<span class="c1"># TensorRT model generated text:  What is parallel programming ?</span>
+<span class="c1"># Pytorch model generated text: The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that</span>
 
-<span class="c1"># The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that</span>
+<span class="c1"># =============================</span>
+<span class="c1"># TensorRT model generated text: The parallel programming paradigm is a set of programming languages that are designed to be used in parallel. The main difference between parallel programming and parallel programming is that</span>
 </pre></div>
 </div>
 <p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes  0.000 seconds)</p>
@@ -575,6 +568,7 @@ <h1>The output sentences should look like<a class="headerlink" href="#the-output
 </div>
 </div>
 <p class="sphx-glr-signature"><a class="reference external" href="https://sphinx-gallery.github.io">Gallery generated by Sphinx-Gallery</a></p>
+</section>
 </section>
 
 
@@ -585,10 +579,10 @@ <h1>The output sentences should look like<a class="headerlink" href="#the-output
   
     <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
       
-        <a href="torch_export_llama2.html" class="btn btn-neutral float-right" title="Compiling Llama2 using the Torch-TensorRT with dynamo backend" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
+        <a href="torch_export_llama2.html" class="btn btn-neutral float-right" title="Compiling Llama2 using the dynamo backend" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
-        <a href="mutable_torchtrt_module_example.html" class="btn btn-neutral" title="Mutable Torch TensorRT Module" accesskey="p" rel="prev"><img src="../../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
+        <a href="torch_compile_stable_diffusion.html" class="btn btn-neutral" title="Compiling Stable Diffusion model using the torch.compile backend" accesskey="p" rel="prev"><img src="../../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
       
     </div>
   
@@ -620,13 +614,12 @@ <h1>The output sentences should look like<a class="headerlink" href="#the-output
           <div class="pytorch-right-menu" id="pytorch-right-menu">
             <div class="pytorch-side-scroll" id="pytorch-side-scroll-right">
               <ul>
-<li><a class="reference internal" href="#">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a><ul>
+<li><a class="reference internal" href="#">Compiling GPT2 using the dynamo backend</a><ul>
 <li><a class="reference internal" href="#imports-and-model-definition">Imports and Model Definition</a></li>
 <li><a class="reference internal" href="#compilation-with-torch-tensorrt-using-dynamo-backend-and-generate-tensorrt-outputs">Compilation with <cite>Torch-TensorRT</cite> using dynamo backend and generate TensorRT outputs</a></li>
 <li><a class="reference internal" href="#decode-the-output-sentences-of-pytorch-and-tensorrt">Decode the output sentences of PyTorch and TensorRT</a></li>
 </ul>
 </li>
-<li><a class="reference internal" href="#the-output-sentences-should-look-like">The output sentences should look like</a></li>
 </ul>
 
             </div>
diff --git a/docs/tutorials/_rendered_examples/dynamo/torch_export_llama2.html b/docs/tutorials/_rendered_examples/dynamo/torch_export_llama2.html
index 1b9adde408..7cc21f8bcc 100644
--- a/docs/tutorials/_rendered_examples/dynamo/torch_export_llama2.html
+++ b/docs/tutorials/_rendered_examples/dynamo/torch_export_llama2.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Compiling Llama2 using the Torch-TensorRT with dynamo backend &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Compiling Llama2 using the dynamo backend &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -39,8 +39,8 @@
   <link rel="stylesheet" href="../../../_static/css/custom.css" type="text/css" />
     <link rel="index" title="Index" href="../../../genindex.html" />
     <link rel="search" title="Search" href="../../../search.html" />
-    <link rel="next" title="torch_tensorrt" href="../../../py_api/torch_tensorrt.html" />
-    <link rel="prev" title="Compiling GPT2 using the Torch-TensorRT with dynamo backend" href="torch_export_gpt2.html" />
+    <link rel="next" title="Legacy notebooks" href="../../notebooks.html" />
+    <link rel="prev" title="Compiling GPT2 using the dynamo backend" href="torch_export_gpt2.html" />
   <!-- Google Tag Manager -->
     <script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':
     new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul class="current">
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1 current"><a class="current reference internal" href="#">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -428,7 +425,7 @@
       </li>
 
         
-      <li>Compiling Llama2 using the Torch-TensorRT with dynamo backend</li>
+      <li>Compiling Llama2 using the dynamo backend</li>
     
     
       <li class="pytorch-breadcrumbs-aside">
@@ -469,9 +466,9 @@
 <p><a class="reference internal" href="#sphx-glr-download-tutorials-rendered-examples-dynamo-torch-export-llama2-py"><span class="std std-ref">Go to the end</span></a>
 to download the full example code</p>
 </div>
-<section class="sphx-glr-example-title" id="compiling-llama2-using-the-torch-tensorrt-with-dynamo-backend">
-<span id="torch-export-llama2"></span><span id="sphx-glr-tutorials-rendered-examples-dynamo-torch-export-llama2-py"></span><h1>Compiling Llama2 using the Torch-TensorRT with dynamo backend<a class="headerlink" href="#compiling-llama2-using-the-torch-tensorrt-with-dynamo-backend" title="Permalink to this heading">¶</a></h1>
-<p>This interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo backend on a Llama2 model.</p>
+<section class="sphx-glr-example-title" id="compiling-llama2-using-the-dynamo-backend">
+<span id="torch-export-llama2"></span><span id="sphx-glr-tutorials-rendered-examples-dynamo-torch-export-llama2-py"></span><h1>Compiling Llama2 using the dynamo backend<a class="headerlink" href="#compiling-llama2-using-the-dynamo-backend" title="Permalink to this heading">¶</a></h1>
+<p>This script illustrates Torch-TensorRT workflow with dynamo backend on popular Llama2 model.</p>
 <section id="imports-and-model-definition">
 <h2>Imports and Model Definition<a class="headerlink" href="#imports-and-model-definition" title="Permalink to this heading">¶</a></h2>
 <div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">torch</span>
@@ -556,16 +553,17 @@ <h2>Decode the output sentences of PyTorch and TensorRT<a class="headerlink" hre
         <span class="n">clean_up_tokenization_spaces</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
     <span class="p">)[</span><span class="mi">0</span><span class="p">],</span>
 <span class="p">)</span>
+
+
+<span class="c1"># Prompt : What is dynamic programming?</span>
+
+<span class="c1"># =============================</span>
+<span class="c1"># Pytorch model generated text: Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</span>
+
+<span class="c1"># =============================</span>
+<span class="c1"># TensorRT model generated text: Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</span>
 </pre></div>
 </div>
-</section>
-</section>
-<section id="the-output-sentences-should-look-like">
-<h1>The output sentences should look like<a class="headerlink" href="#the-output-sentences-should-look-like" title="Permalink to this heading">¶</a></h1>
-</section>
-<section id="pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">
-<h1>Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and<a class="headerlink" href="#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and" title="Permalink to this heading">¶</a></h1>
-<p>TensorRT model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</p>
 <p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes  0.000 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-tutorials-rendered-examples-dynamo-torch-export-llama2-py">
 <div class="sphx-glr-download sphx-glr-download-python docutils container">
@@ -576,6 +574,7 @@ <h1>Pytorch model generated text:  Dynamic programming is an algorithmic techniq
 </div>
 </div>
 <p class="sphx-glr-signature"><a class="reference external" href="https://sphinx-gallery.github.io">Gallery generated by Sphinx-Gallery</a></p>
+</section>
 </section>
 
 
@@ -586,10 +585,10 @@ <h1>Pytorch model generated text:  Dynamic programming is an algorithmic techniq
   
     <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
       
-        <a href="../../../py_api/torch_tensorrt.html" class="btn btn-neutral float-right" title="torch_tensorrt" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
+        <a href="../../notebooks.html" class="btn btn-neutral float-right" title="Legacy notebooks" accesskey="n" rel="next">Next <img src="../../../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
-        <a href="torch_export_gpt2.html" class="btn btn-neutral" title="Compiling GPT2 using the Torch-TensorRT with dynamo backend" accesskey="p" rel="prev"><img src="../../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
+        <a href="torch_export_gpt2.html" class="btn btn-neutral" title="Compiling GPT2 using the dynamo backend" accesskey="p" rel="prev"><img src="../../../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
       
     </div>
   
@@ -621,14 +620,12 @@ <h1>Pytorch model generated text:  Dynamic programming is an algorithmic techniq
           <div class="pytorch-right-menu" id="pytorch-right-menu">
             <div class="pytorch-side-scroll" id="pytorch-side-scroll-right">
               <ul>
-<li><a class="reference internal" href="#">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a><ul>
+<li><a class="reference internal" href="#">Compiling Llama2 using the dynamo backend</a><ul>
 <li><a class="reference internal" href="#imports-and-model-definition">Imports and Model Definition</a></li>
 <li><a class="reference internal" href="#compilation-with-torch-tensorrt-using-dynamo-backend-and-generate-tensorrt-outputs">Compilation with <cite>Torch-TensorRT</cite> using dynamo backend and generate TensorRT outputs</a></li>
 <li><a class="reference internal" href="#decode-the-output-sentences-of-pytorch-and-tensorrt">Decode the output sentences of PyTorch and TensorRT</a></li>
 </ul>
 </li>
-<li><a class="reference internal" href="#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li><a class="reference internal" href="#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
 </ul>
 
             </div>
diff --git a/docs/tutorials/_rendered_examples/dynamo/vgg16_ptq.html b/docs/tutorials/_rendered_examples/dynamo/vgg16_ptq.html
index 88dac50372..968de093b6 100644
--- a/docs/tutorials/_rendered_examples/dynamo/vgg16_ptq.html
+++ b/docs/tutorials/_rendered_examples/dynamo/vgg16_ptq.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Deploy Quantized Models using Torch-TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Deploy Quantized Models using Torch-TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1 current"><a class="current reference internal" href="#">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/tutorials/_rendered_examples/index.html b/docs/tutorials/_rendered_examples/index.html
index ef6072a9f5..572111dbff 100644
--- a/docs/tutorials/_rendered_examples/index.html
+++ b/docs/tutorials/_rendered_examples/index.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Torch-TensorRT Tutorials &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Torch-TensorRT Tutorials &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -273,7 +273,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -318,6 +318,11 @@
 <li class="toctree-l1"><a class="reference internal" href="dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -337,22 +342,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -464,13 +461,7 @@
               
   <section id="torch-tensorrt-tutorials">
 <span id="id1"></span><h1>Torch-TensorRT Tutorials<a class="headerlink" href="#torch-tensorrt-tutorials" title="Permalink to this heading">¶</a></h1>
-<p>The user guide covers the basic concepts and usage of Torch-TensorRT.
-We also provide a number of tutorials to explore specific usecases and advanced concepts</p>
-<div class="sphx-glr-thumbnails"></div></section>
-<section id="torch-tensorrt-examples">
-<h1>Torch-TensorRT Examples<a class="headerlink" href="#torch-tensorrt-examples" title="Permalink to this heading">¶</a></h1>
-<p>Please refer to the following examples which demonstrate the usage of different features of Torch-TensorRT. We also provide
-examples of Torch-TensorRT compilation of select computer vision and language models.</p>
+<div class="sphx-glr-thumbnails"></div><p>Here we provide examples of Torch-TensorRT compilation of popular computer vision and language models.</p>
 <section id="dependencies">
 <h2>Dependencies<a class="headerlink" href="#dependencies" title="Permalink to this heading">¶</a></h2>
 <p>Please install the following external dependencies (assuming you already have correct <cite>torch</cite>, <cite>torch_tensorrt</cite> and <cite>tensorrt</cite> libraries installed (<a class="reference external" href="https://github.com/pytorch/TensorRT?tab=readme-ov-file#dependencies">dependencies</a>))</p>
@@ -478,32 +469,18 @@ <h2>Dependencies<a class="headerlink" href="#dependencies" title="Permalink to t
 </pre></div>
 </div>
 </section>
-<section id="compiler-features">
-<h2>Compiler Features<a class="headerlink" href="#compiler-features" title="Permalink to this heading">¶</a></h2>
-<ul class="simple">
-<li><p><a class="reference internal" href="dynamo/torch_compile_advanced_usage.html#torch-compile-advanced-usage"><span class="std std-ref">Torch Compile Advanced Usage</span></a>: Advanced usage including making a custom backend to use directly with the <code class="docutils literal notranslate"><span class="pre">torch.compile</span></code> API</p></li>
-<li><p><a class="reference internal" href="dynamo/torch_export_cudagraphs.html#torch-export-cudagraphs"><span class="std std-ref">Torch Export with Cudagraphs</span></a>: Using the Cudagraphs integration with <cite>ir=”dynamo”</cite></p></li>
-<li><p><a class="reference internal" href="dynamo/converter_overloading.html#converter-overloading"><span class="std std-ref">Overloading Torch-TensorRT Converters with Custom Converters</span></a>: How to write custom converters and overload existing ones</p></li>
-<li><p><a class="reference internal" href="dynamo/custom_kernel_plugins.html#custom-kernel-plugins"><span class="std std-ref">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</span></a>: Creating a plugin to use a custom kernel inside TensorRT engines</p></li>
-<li><p><a class="reference internal" href="dynamo/refit_engine_example.html#refit-engine-example"><span class="std std-ref">Refitting Torch-TensorRT Programs with New Weights</span></a>: Refitting a compiled TensorRT Graph Module with updated weights</p></li>
-<li><p><a class="reference internal" href="dynamo/mutable_torchtrt_module_example.html#mutable-torchtrt-module-example"><span class="std std-ref">Mutable Torch TensorRT Module</span></a>: Compile, use, and modify TensorRT Graph Module with MutableTorchTensorRTModule</p></li>
-<li><p><span class="xref std std-ref">vgg16_fp8_ptq</span>: Compiling a VGG16 model with FP8 and PTQ using <code class="docutils literal notranslate"><span class="pre">torch.compile</span></code></p></li>
-<li><p><a class="reference internal" href="dynamo/engine_caching_example.html#engine-caching-example"><span class="std std-ref">Engine Caching</span></a>: Utilizing engine caching to speed up compilation times</p></li>
-<li><p><a class="reference internal" href="dynamo/engine_caching_bert_example.html#engine-caching-bert-example"><span class="std std-ref">Engine Caching (BERT)</span></a>: Demonstrating engine caching on BERT</p></li>
-</ul>
-</section>
 <section id="model-zoo">
 <h2>Model Zoo<a class="headerlink" href="#model-zoo" title="Permalink to this heading">¶</a></h2>
 <ul class="simple">
-<li><p><a class="reference internal" href="dynamo/torch_compile_resnet_example.html#torch-compile-resnet"><span class="std std-ref">Compiling ResNet using the Torch-TensorRT torch.compile Backend</span></a>: Compiling a ResNet model using the Torch Compile Frontend for <code class="docutils literal notranslate"><span class="pre">torch_tensorrt.compile</span></code></p></li>
-<li><p><a class="reference internal" href="dynamo/torch_compile_transformers_example.html#torch-compile-transformer"><span class="std std-ref">Compiling a Transformer using torch.compile and TensorRT</span></a>: Compiling a Transformer model using <code class="docutils literal notranslate"><span class="pre">torch.compile</span></code></p></li>
-<li><p><a class="reference internal" href="dynamo/torch_compile_stable_diffusion.html#torch-compile-stable-diffusion"><span class="std std-ref">Torch Compile Stable Diffusion</span></a>: Compiling a Stable Diffusion model using <code class="docutils literal notranslate"><span class="pre">torch.compile</span></code></p></li>
+<li><p><a class="reference internal" href="dynamo/torch_compile_resnet_example.html#torch-compile-resnet"><span class="std std-ref">Compiling ResNet with dynamic shapes using the torch.compile backend</span></a>: Compiling a ResNet model using the Torch Compile Frontend for <code class="docutils literal notranslate"><span class="pre">torch_tensorrt.compile</span></code></p></li>
+<li><p><a class="reference internal" href="dynamo/torch_compile_transformers_example.html#torch-compile-transformer"><span class="std std-ref">Compiling BERT using the torch.compile backend</span></a>: Compiling a Transformer model using <code class="docutils literal notranslate"><span class="pre">torch.compile</span></code></p></li>
+<li><p><a class="reference internal" href="dynamo/torch_compile_stable_diffusion.html#torch-compile-stable-diffusion"><span class="std std-ref">Compiling Stable Diffusion model using the torch.compile backend</span></a>: Compiling a Stable Diffusion model using <code class="docutils literal notranslate"><span class="pre">torch.compile</span></code></p></li>
 <li><p><span class="xref std std-ref">_torch_export_gpt2</span>: Compiling a GPT2 model using AOT workflow (<cite>ir=dynamo</cite>)</p></li>
 <li><p><span class="xref std std-ref">_torch_export_llama2</span>: Compiling a Llama2 model using AOT workflow (<cite>ir=dynamo</cite>)</p></li>
 </ul>
 <div class="sphx-glr-thumbnails"><div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with torch.compi..."><img alt="" src="../../_images/sphx_glr_torch_compile_stable_diffusion_thumb.png" />
-<p><a class="reference internal" href="dynamo/torch_compile_stable_diffusion.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-stable-diffusion-py"><span class="std std-ref">Torch Compile Stable Diffusion</span></a></p>
-  <div class="sphx-glr-thumbnail-title">Torch Compile Stable Diffusion</div>
+<p><a class="reference internal" href="dynamo/torch_compile_stable_diffusion.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-stable-diffusion-py"><span class="std std-ref">Compiling Stable Diffusion model using the torch.compile backend</span></a></p>
+  <div class="sphx-glr-thumbnail-title">Compiling Stable Diffusion model using the torch.compile backend</div>
 </div><div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as an overview of the process by which the Torch-TensorRT C..."><img alt="" src="../../_images/sphx_glr_torch_export_cudagraphs_thumb.png" />
 <p><a class="reference internal" href="dynamo/torch_export_cudagraphs.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-export-cudagraphs-py"><span class="std std-ref">Torch Export with Cudagraphs</span></a></p>
   <div class="sphx-glr-thumbnail-title">Torch Export with Cudagraphs</div>
@@ -511,26 +488,26 @@ <h2>Model Zoo<a class="headerlink" href="#model-zoo" title="Permalink to this he
 <p><a class="reference internal" href="dynamo/refit_engine_example.html#sphx-glr-tutorials-rendered-examples-dynamo-refit-engine-example-py"><span class="std std-ref">Refitting Torch-TensorRT Programs with New Weights</span></a></p>
   <div class="sphx-glr-thumbnail-title">Refitting Torch-TensorRT Programs with New Weights</div>
 </div><div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with torch.compi..."><img alt="" src="../../_images/sphx_glr_torch_compile_transformers_example_thumb.png" />
-<p><a class="reference internal" href="dynamo/torch_compile_transformers_example.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-transformers-example-py"><span class="std std-ref">Compiling a Transformer using torch.compile and TensorRT</span></a></p>
-  <div class="sphx-glr-thumbnail-title">Compiling a Transformer using torch.compile and TensorRT</div>
+<p><a class="reference internal" href="dynamo/torch_compile_transformers_example.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-transformers-example-py"><span class="std std-ref">Compiling BERT using the torch.compile backend</span></a></p>
+  <div class="sphx-glr-thumbnail-title">Compiling BERT using the torch.compile backend</div>
 </div><div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as an overview of the process by which torch_tensorrt.compi..."><img alt="" src="../../_images/sphx_glr_torch_compile_advanced_usage_thumb.png" />
 <p><a class="reference internal" href="dynamo/torch_compile_advanced_usage.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-advanced-usage-py"><span class="std std-ref">Torch Compile Advanced Usage</span></a></p>
   <div class="sphx-glr-thumbnail-title">Torch Compile Advanced Usage</div>
 </div><div class="sphx-glr-thumbcontainer" tooltip="Small caching example on BERT."><img alt="" src="../../_images/sphx_glr_engine_caching_bert_example_thumb.png" />
 <p><a class="reference internal" href="dynamo/engine_caching_bert_example.html#sphx-glr-tutorials-rendered-examples-dynamo-engine-caching-bert-example-py"><span class="std std-ref">Engine Caching (BERT)</span></a></p>
   <div class="sphx-glr-thumbnail-title">Engine Caching (BERT)</div>
-</div><div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo back..."><img alt="" src="../../_images/sphx_glr_torch_export_llama2_thumb.png" />
-<p><a class="reference internal" href="dynamo/torch_export_llama2.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-export-llama2-py"><span class="std std-ref">Compiling Llama2 using the Torch-TensorRT with dynamo backend</span></a></p>
-  <div class="sphx-glr-thumbnail-title">Compiling Llama2 using the Torch-TensorRT with dynamo backend</div>
 </div><div class="sphx-glr-thumbcontainer" tooltip="We are going to demonstrate how we can easily use Mutable Torch TensorRT Module to compile, int..."><img alt="" src="../../_images/sphx_glr_mutable_torchtrt_module_example_thumb.png" />
 <p><a class="reference internal" href="dynamo/mutable_torchtrt_module_example.html#sphx-glr-tutorials-rendered-examples-dynamo-mutable-torchtrt-module-example-py"><span class="std std-ref">Mutable Torch TensorRT Module</span></a></p>
   <div class="sphx-glr-thumbnail-title">Mutable Torch TensorRT Module</div>
 </div><div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with torch.compi..."><img alt="" src="../../_images/sphx_glr_torch_compile_resnet_example_thumb.png" />
-<p><a class="reference internal" href="dynamo/torch_compile_resnet_example.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-resnet-example-py"><span class="std std-ref">Compiling ResNet using the Torch-TensorRT torch.compile Backend</span></a></p>
-  <div class="sphx-glr-thumbnail-title">Compiling ResNet using the Torch-TensorRT torch.compile Backend</div>
-</div><div class="sphx-glr-thumbcontainer" tooltip="This interactive script is intended as a sample of the Torch-TensorRT workflow with dynamo back..."><img alt="" src="../../_images/sphx_glr_torch_export_gpt2_thumb.png" />
-<p><a class="reference internal" href="dynamo/torch_export_gpt2.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-export-gpt2-py"><span class="std std-ref">Compiling GPT2 using the Torch-TensorRT with dynamo backend</span></a></p>
-  <div class="sphx-glr-thumbnail-title">Compiling GPT2 using the Torch-TensorRT with dynamo backend</div>
+<p><a class="reference internal" href="dynamo/torch_compile_resnet_example.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-compile-resnet-example-py"><span class="std std-ref">Compiling ResNet with dynamic shapes using the torch.compile backend</span></a></p>
+  <div class="sphx-glr-thumbnail-title">Compiling ResNet with dynamic shapes using the torch.compile backend</div>
+</div><div class="sphx-glr-thumbcontainer" tooltip="This script illustrates Torch-TensorRT workflow with dynamo backend on popular GPT2 model."><img alt="" src="../../_images/sphx_glr_torch_export_gpt2_thumb.png" />
+<p><a class="reference internal" href="dynamo/torch_export_gpt2.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-export-gpt2-py"><span class="std std-ref">Compiling GPT2 using the dynamo backend</span></a></p>
+  <div class="sphx-glr-thumbnail-title">Compiling GPT2 using the dynamo backend</div>
+</div><div class="sphx-glr-thumbcontainer" tooltip="This script illustrates Torch-TensorRT workflow with dynamo backend on popular Llama2 model."><img alt="" src="../../_images/sphx_glr_torch_export_llama2_thumb.png" />
+<p><a class="reference internal" href="dynamo/torch_export_llama2.html#sphx-glr-tutorials-rendered-examples-dynamo-torch-export-llama2-py"><span class="std std-ref">Compiling Llama2 using the dynamo backend</span></a></p>
+  <div class="sphx-glr-thumbnail-title">Compiling Llama2 using the dynamo backend</div>
 </div><div class="sphx-glr-thumbcontainer" tooltip="If for some reason you want to change the conversion behavior of a specific PyTorch operation t..."><img alt="" src="../../_images/sphx_glr_converter_overloading_thumb.png" />
 <p><a class="reference internal" href="dynamo/converter_overloading.html#sphx-glr-tutorials-rendered-examples-dynamo-converter-overloading-py"><span class="std std-ref">Overloading Torch-TensorRT Converters with Custom Converters</span></a></p>
   <div class="sphx-glr-thumbnail-title">Overloading Torch-TensorRT Converters with Custom Converters</div>
@@ -591,10 +568,8 @@ <h2>Model Zoo<a class="headerlink" href="#model-zoo" title="Permalink to this he
           <div class="pytorch-right-menu" id="pytorch-right-menu">
             <div class="pytorch-side-scroll" id="pytorch-side-scroll-right">
               <ul>
-<li><a class="reference internal" href="#">Torch-TensorRT Tutorials</a></li>
-<li><a class="reference internal" href="#torch-tensorrt-examples">Torch-TensorRT Examples</a><ul>
+<li><a class="reference internal" href="#">Torch-TensorRT Tutorials</a><ul>
 <li><a class="reference internal" href="#dependencies">Dependencies</a></li>
-<li><a class="reference internal" href="#compiler-features">Compiler Features</a></li>
 <li><a class="reference internal" href="#model-zoo">Model Zoo</a></li>
 </ul>
 </li>
diff --git a/docs/tutorials/notebooks.html b/docs/tutorials/notebooks.html
index d911a95e7f..0b6866bd5e 100644
--- a/docs/tutorials/notebooks.html
+++ b/docs/tutorials/notebooks.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Example notebooks &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Legacy notebooks &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -39,8 +39,8 @@
   <link rel="stylesheet" href="../_static/css/custom.css" type="text/css" />
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
-    <link rel="next" title="Compiling ResNet using the Torch-TensorRT torch.compile Backend" href="_rendered_examples/dynamo/torch_compile_resnet_example.html" />
-    <link rel="prev" title="Serving a Torch-TensorRT model with Triton" href="serving_torch_tensorrt_with_triton.html" />
+    <link rel="next" title="torch_tensorrt" href="../py_api/torch_tensorrt.html" />
+    <link rel="prev" title="Compiling Llama2 using the dynamo backend" href="_rendered_examples/dynamo/torch_export_llama2.html" />
   <!-- Google Tag Manager -->
     <script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':
     new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul class="current">
-<li class="toctree-l1"><a class="reference internal" href="serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1 current"><a class="current reference internal" href="#">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -428,7 +425,7 @@
       </li>
 
         
-      <li>Example notebooks</li>
+      <li>Legacy notebooks</li>
     
     
       <li class="pytorch-breadcrumbs-aside">
@@ -464,10 +461,9 @@
             <div role="main" class="main-content" itemscope="itemscope" itemtype="http://schema.org/Article">
              <article itemprop="articleBody" id="pytorch-article" class="pytorch-article">
               
-  <section id="example-notebooks">
-<span id="notebooks"></span><h1>Example notebooks<a class="headerlink" href="#example-notebooks" title="Permalink to this heading">¶</a></h1>
-<p>There exists a number of notebooks which cover specific using specific features and models
-with Torch-TensorRT</p>
+  <section id="legacy-notebooks">
+<span id="notebooks"></span><h1>Legacy notebooks<a class="headerlink" href="#legacy-notebooks" title="Permalink to this heading">¶</a></h1>
+<p>There exists a number of notebooks which demonstrate different model conversions / features / frontends available within Torch-TensorRT</p>
 <section id="id1">
 <h2>Notebooks<a class="headerlink" href="#id1" title="Permalink to this heading">¶</a></h2>
 <section id="compiling-citrinet-with-torch-tensorrt">
@@ -611,10 +607,10 @@ <h3>Deploying Quantization Aware Trained models in INT8 using Torch-TensorRT<a c
   
     <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
       
-        <a href="_rendered_examples/dynamo/torch_compile_resnet_example.html" class="btn btn-neutral float-right" title="Compiling ResNet using the Torch-TensorRT torch.compile Backend" accesskey="n" rel="next">Next <img src="../_static/images/chevron-right-orange.svg" class="next-page"></a>
+        <a href="../py_api/torch_tensorrt.html" class="btn btn-neutral float-right" title="torch_tensorrt" accesskey="n" rel="next">Next <img src="../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
-        <a href="serving_torch_tensorrt_with_triton.html" class="btn btn-neutral" title="Serving a Torch-TensorRT model with Triton" accesskey="p" rel="prev"><img src="../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
+        <a href="_rendered_examples/dynamo/torch_export_llama2.html" class="btn btn-neutral" title="Compiling Llama2 using the dynamo backend" accesskey="p" rel="prev"><img src="../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
       
     </div>
   
@@ -646,7 +642,7 @@ <h3>Deploying Quantization Aware Trained models in INT8 using Torch-TensorRT<a c
           <div class="pytorch-right-menu" id="pytorch-right-menu">
             <div class="pytorch-side-scroll" id="pytorch-side-scroll-right">
               <ul>
-<li><a class="reference internal" href="#">Example notebooks</a><ul>
+<li><a class="reference internal" href="#">Legacy notebooks</a><ul>
 <li><a class="reference internal" href="#id1">Notebooks</a><ul>
 <li><a class="reference internal" href="#compiling-citrinet-with-torch-tensorrt">Compiling CitriNet with Torch-TensorRT</a></li>
 <li><a class="reference internal" href="#compiling-efficientnet-with-torch-tensorrt">Compiling EfficientNet with Torch-TensorRT</a></li>
diff --git a/docs/tutorials/serving_torch_tensorrt_with_triton.html b/docs/tutorials/serving_torch_tensorrt_with_triton.html
index b31e4c7200..ccf6487627 100644
--- a/docs/tutorials/serving_torch_tensorrt_with_triton.html
+++ b/docs/tutorials/serving_torch_tensorrt_with_triton.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Serving a Torch-TensorRT model with Triton &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Serving a Torch-TensorRT model with Triton &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -39,8 +39,8 @@
   <link rel="stylesheet" href="../_static/css/custom.css" type="text/css" />
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
-    <link rel="next" title="Example notebooks" href="notebooks.html" />
-    <link rel="prev" title="Torch-TensorRT (FX Frontend) User Guide" href="../fx/getting_started_with_fx_path.html" />
+    <link rel="next" title="Torch Export with Cudagraphs" href="_rendered_examples/dynamo/torch_export_cudagraphs.html" />
+    <link rel="prev" title="Refitting Torch-TensorRT Programs with New Weights" href="_rendered_examples/dynamo/refit_engine_example.html" />
   <!-- Google Tag Manager -->
     <script>(function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':
     new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -309,7 +309,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../getting_started/quick_start.html">Quick Start</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">User Guide</span></p>
-<ul>
+<ul class="current">
 <li class="toctree-l1"><a class="reference internal" href="../user_guide/torch_tensorrt_explained.html">Torch-TensorRT Explained</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../user_guide/dynamic_shapes.html">Dynamic shapes with Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../user_guide/saving_models.html">Saving models compiled with Torch-TensorRT</a></li>
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1 current"><a class="current reference internal" href="#">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
-<ul class="current">
-<li class="toctree-l1 current"><a class="current reference internal" href="#">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
+<ul>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
@@ -654,10 +651,10 @@ <h2>Step 3: Building a Triton Client to Query the Server<a class="headerlink" hr
   
     <div class="rst-footer-buttons" role="navigation" aria-label="footer navigation">
       
-        <a href="notebooks.html" class="btn btn-neutral float-right" title="Example notebooks" accesskey="n" rel="next">Next <img src="../_static/images/chevron-right-orange.svg" class="next-page"></a>
+        <a href="_rendered_examples/dynamo/torch_export_cudagraphs.html" class="btn btn-neutral float-right" title="Torch Export with Cudagraphs" accesskey="n" rel="next">Next <img src="../_static/images/chevron-right-orange.svg" class="next-page"></a>
       
       
-        <a href="../fx/getting_started_with_fx_path.html" class="btn btn-neutral" title="Torch-TensorRT (FX Frontend) User Guide" accesskey="p" rel="prev"><img src="../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
+        <a href="_rendered_examples/dynamo/refit_engine_example.html" class="btn btn-neutral" title="Refitting Torch-TensorRT Programs with New Weights" accesskey="p" rel="prev"><img src="../_static/images/chevron-right-orange.svg" class="previous-page"> Previous</a>
       
     </div>
   
diff --git a/docs/user_guide/dynamic_shapes.html b/docs/user_guide/dynamic_shapes.html
index 4720410088..db4970aab8 100644
--- a/docs/user_guide/dynamic_shapes.html
+++ b/docs/user_guide/dynamic_shapes.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Dynamic shapes with Torch-TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Dynamic shapes with Torch-TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/user_guide/mixed_precision.html b/docs/user_guide/mixed_precision.html
index 3e316412be..db77f67f72 100644
--- a/docs/user_guide/mixed_precision.html
+++ b/docs/user_guide/mixed_precision.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Compile Mixed Precision models with Torch-TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Compile Mixed Precision models with Torch-TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/user_guide/runtime.html b/docs/user_guide/runtime.html
index dfbdfb449a..2acf763fa9 100644
--- a/docs/user_guide/runtime.html
+++ b/docs/user_guide/runtime.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Deploying Torch-TensorRT Programs &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Deploying Torch-TensorRT Programs &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/user_guide/saving_models.html b/docs/user_guide/saving_models.html
index 717b7c8ce3..815f85da9e 100644
--- a/docs/user_guide/saving_models.html
+++ b/docs/user_guide/saving_models.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Saving models compiled with Torch-TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Saving models compiled with Torch-TensorRT &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/user_guide/torch_tensorrt_explained.html b/docs/user_guide/torch_tensorrt_explained.html
index 85d2edaeb9..9ef4e13ecc 100644
--- a/docs/user_guide/torch_tensorrt_explained.html
+++ b/docs/user_guide/torch_tensorrt_explained.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>Torch-TensorRT Explained &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>Torch-TensorRT Explained &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>
diff --git a/docs/user_guide/using_dla.html b/docs/user_guide/using_dla.html
index efd146653c..2dfdf5b796 100644
--- a/docs/user_guide/using_dla.html
+++ b/docs/user_guide/using_dla.html
@@ -10,7 +10,7 @@
 
   <meta name="viewport" content="width=device-width, initial-scale=1.0">
   
-  <title>DLA &mdash; Torch-TensorRT v2.6.0.dev0+743fdbd documentation</title>
+  <title>DLA &mdash; Torch-TensorRT v2.6.0.dev0+2c517be documentation</title>
   
 
   
@@ -275,7 +275,7 @@
               
               
                 <div class="version">
-                  v2.6.0.dev0+743fdbd
+                  v2.6.0.dev0+2c517be
                 </div>
               
             
@@ -320,6 +320,11 @@
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/vgg16_ptq.html">Deploy Quantized Models using Torch-TensorRT</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/engine_caching_example.html">Engine Caching</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/refit_engine_example.html">Refitting Torch-TensorRT Programs with New Weights</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Dynamo Frontend</span></p>
 <ul>
@@ -339,22 +344,14 @@
 <ul>
 <li class="toctree-l1"><a class="reference internal" href="../fx/getting_started_with_fx_path.html">Torch-TensorRT (FX Frontend) User Guide</a></li>
 </ul>
-<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
+<p class="caption" role="heading"><span class="caption-text">Model Zoo</span></p>
 <ul>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/serving_torch_tensorrt_with_triton.html">Serving a Torch-TensorRT model with Triton</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Example notebooks</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet using the Torch-TensorRT <cite>torch.compile</cite> Backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling a Transformer using torch.compile and TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Torch Compile Stable Diffusion</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_cudagraphs.html">Torch Export with Cudagraphs</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/converter_overloading.html">Overloading Torch-TensorRT Converters with Custom Converters</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/custom_kernel_plugins.html">Using Custom Kernels within TensorRT Engines with Torch-TensorRT</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/mutable_torchtrt_module_example.html">Mutable Torch TensorRT Module</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the Torch-TensorRT with dynamo backend</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#the-output-sentences-should-look-like">The output sentences should look like</a></li>
-<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html#pytorch-model-generated-text-dynamic-programming-is-an-algorithmic-technique-used-to-solve-complex-problems-by-breaking-them-down-into-smaller-subproblems-solving-each-subproblem-only-once-and">Pytorch model generated text:  Dynamic programming is an algorithmic technique used to solve complex problems by breaking them down into smaller subproblems, solving each subproblem only once, and</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_resnet_example.html">Compiling ResNet with dynamic shapes using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_transformers_example.html">Compiling BERT using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_compile_stable_diffusion.html">Compiling Stable Diffusion model using the <cite>torch.compile</cite> backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_gpt2.html">Compiling GPT2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/_rendered_examples/dynamo/torch_export_llama2.html">Compiling Llama2 using the dynamo backend</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../tutorials/notebooks.html">Legacy notebooks</a></li>
 </ul>
 <p class="caption" role="heading"><span class="caption-text">Python API Documentation</span></p>
 <ul>