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<h1>Home</h1>

<p><img alt="Python" src="https://img.shields.io/badge/Python-3.10%20|%203.11%20|%203.12-brightgreen?style=for-the-badge" />
<p><a href="https://pypi.org/project/xinfer/"><img alt="Python" src="https://img.shields.io/badge/Python-3.10+-brightgreen?style=for-the-badge&amp;logo=python&amp;logoColor=white" /></a>
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<br />
<a href="https://dnth.github.io/x.infer" target="_blank" rel="noopener noreferrer"><strong>Explore the docs »</strong></a>
<br />
<a href="#quickstart" target="_blank" rel="noopener noreferrer">Quickstart</a>
<a href="#-quickstart" target="_blank" rel="noopener noreferrer">Quickstart</a>
·
<a href="https://github.com/dnth/x.infer/issues/new?assignees=&labels=Feature+Request&projects=&template=feature_request.md" target="_blank" rel="noopener noreferrer">Feature Request</a>
·
Expand All @@ -457,18 +457,51 @@ <h1>Home</h1>
<a href="https://dicksonneoh.com/" target="_blank" rel="noopener noreferrer">About</a>
</div>

<h2 id="why-xinfer">Why x.infer?<a class="headerlink" href="#why-xinfer" title="Permanent link">&para;</a></h2>
<p>If you'd like to run many models from different libraries without having to rewrite your inference code, x.infer is for you. It has a simple API and is easy to extend. Currently supports Transformers, Ultralytics, and TIMM.</p>
<p>Have a custom model? Create a class that implements the <code>BaseModel</code> interface and register it with x.infer. See <a href="#adding-new-models">Adding New Models</a> for more details.</p>
<h2 id="key-features">Key Features<a class="headerlink" href="#key-features" title="Permanent link">&para;</a></h2>
<div align="center">
<img src="https://raw.githubusercontent.com/dnth/x.infer/refs/heads/main/assets/flowchart.gif" alt="x.infer" width="500"/>
<br />

</div>

<h2 id="why-xinfer">🤔 Why x.infer?<a class="headerlink" href="#why-xinfer" title="Permanent link">&para;</a></h2>
<p>So, a new computer vision model just dropped last night. It's called <code>GPT-54o-mini-vision-pro-max-xxxl</code>. It's a super cool model, open-source, open-weights, open-data, all the good stuff.</p>
<p>You're excited. You want to try it out. </p>
<p>But it's written in a new framework, <code>TyPorch</code> that you know nothing about.
You don't want to spend a weekend learning <code>TyPorch</code> just to find out the model is not what you expected.</p>
<p>This is where x.infer comes in. </p>
<p>x.infer is a simple library that allows you to run inference with any computer vision model in just a few lines of code. All in Python.</p>
<p>Out of the box, x.infer supports the following frameworks:</p>
<p><a href="https://github.com/huggingface/transformers"><img alt="Transformers" src="https://img.shields.io/github/stars/huggingface/transformers?style=for-the-badge&amp;logo=huggingface&amp;label=Transformers%20⭐&amp;color=yellow" /></a>
<a href="https://github.com/huggingface/pytorch-image-models"><img alt="TIMM" src="https://img.shields.io/github/stars/huggingface/pytorch-image-models?style=for-the-badge&amp;logo=pytorch&amp;label=TIMM%20⭐&amp;color=limegreen" /></a>
<a href="https://github.com/ultralytics/ultralytics"><img alt="Ultralytics" src="https://img.shields.io/github/stars/ultralytics/ultralytics?style=for-the-badge&amp;logo=udacity&amp;label=Ultralytics%20⭐&amp;color=red" /></a>
<a href="https://github.com/vllm-project/vllm"><img alt="vLLM" src="https://img.shields.io/github/stars/vllm-project/vllm?style=for-the-badge&amp;logo=v&amp;label=vLLM%20⭐&amp;color=purple" /></a>
<a href="https://github.com/ollama/ollama"><img alt="Ollama" src="https://img.shields.io/github/stars/ollama/ollama?style=for-the-badge&amp;logo=ollama&amp;label=Ollama%20⭐&amp;color=darkgreen" /></a></p>
<p>Combined, x.infer supports over 1000+ models from all the above frameworks.</p>
<p>Tasks supported:</p>
<p><img alt="Image Classification" src="https://img.shields.io/badge/Image%20Classification-blueviolet?style=for-the-badge" />
<img alt="Object Detection" src="https://img.shields.io/badge/Object%20Detection-coral?style=for-the-badge" />
<img alt="Image to Text" src="https://img.shields.io/badge/Image%20to%20Text-gold?style=for-the-badge" /></p>
<p>Run any supported model using the following 4 lines of code:</p>
<div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">1</span>
<span class="normal">2</span>
<span class="normal">3</span>
<span class="normal">4</span>
<span class="normal">5</span>
<span class="normal">6</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="kn">import</span> <span class="nn">xinfer</span>

<span class="n">model</span> <span class="o">=</span> <span class="n">xinfer</span><span class="o">.</span><span class="n">create_model</span><span class="p">(</span><span class="s2">&quot;vikhyatk/moondream2&quot;</span><span class="p">)</span>
<span class="n">model</span><span class="o">.</span><span class="n">infer</span><span class="p">(</span><span class="n">image</span><span class="p">,</span> <span class="n">prompt</span><span class="p">)</span> <span class="c1"># Run single inference</span>
<span class="n">model</span><span class="o">.</span><span class="n">infer_batch</span><span class="p">(</span><span class="n">images</span><span class="p">,</span> <span class="n">prompts</span><span class="p">)</span> <span class="c1"># Run batch inference</span>
<span class="n">model</span><span class="o">.</span><span class="n">launch_gradio</span><span class="p">()</span> <span class="c1"># Launch Gradio interface</span>
</code></pre></div></td></tr></table></div>
<p>Have a custom model? Create a class that implements the <code>BaseModel</code> interface and register it with x.infer. See <a href="#add-your-own-model">Add Your Own Model</a> for more details.</p>
<h2 id="key-features">🌟 Key Features<a class="headerlink" href="#key-features" title="Permanent link">&para;</a></h2>
<div align="center">
<img src="https://raw.githubusercontent.com/dnth/x.infer/refs/heads/main/assets/flowchart.gif" alt="x.infer" width="900"/>
</div>

<ul>
<li><strong>Unified Interface:</strong> Interact with different machine learning models through a single, consistent API.</li>
<li><strong>Unified Interface:</strong> Interact with different computer vision frameworks through a single, consistent API.</li>
<li><strong>Modular Design:</strong> Integrate and swap out models without altering the core framework.</li>
<li><strong>Ease of Use:</strong> Simplifies model loading, input preprocessing, inference execution, and output postprocessing.</li>
<li><strong>Extensibility:</strong> Add support for new models and libraries with minimal code changes.</li>
</ul>

Expand All @@ -493,7 +526,7 @@ <h2 id="key-features">Key Features<a class="headerlink" href="#key-features" tit
<span class="md-icon" title="Last update">
<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 24 24"><path d="M21 13.1c-.1 0-.3.1-.4.2l-1 1 2.1 2.1 1-1c.2-.2.2-.6 0-.8l-1.3-1.3c-.1-.1-.2-.2-.4-.2m-1.9 1.8-6.1 6V23h2.1l6.1-6.1zM12.5 7v5.2l4 2.4-1 1L11 13V7zM11 21.9c-5.1-.5-9-4.8-9-9.9C2 6.5 6.5 2 12 2c5.3 0 9.6 4.1 10 9.3-.3-.1-.6-.2-1-.2s-.7.1-1 .2C19.6 7.2 16.2 4 12 4c-4.4 0-8 3.6-8 8 0 4.1 3.1 7.5 7.1 7.9l-.1.2z"/></svg>
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<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-timeago"><span class="timeago" datetime="2024-10-21T15:31:57+00:00" locale="en"></span></span><span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-iso_date">2024-10-21</span>
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-timeago"><span class="timeago" datetime="2024-11-02T15:36:02+00:00" locale="en"></span></span><span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-iso_date">2024-11-02</span>
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