diff --git a/build/gtsrb/README.md b/build/gtsrb/README.md
new file mode 100644
index 0000000..f5179a1
--- /dev/null
+++ b/build/gtsrb/README.md
@@ -0,0 +1,26 @@
+# Brevitas GTSRB example
+
+This is the binarized CNV topology from the paper [FINN: A Framework for Fast, Scalable Binarized Neural Network Inference](https://arxiv.org/abs/1612.07119) which is trained
+on the [German Traffic Sign Recognition Benchmark (GTSRB)](https://benchmark.ini.rub.de/gtsrb_news.html) dataset.
+
+## Build bitfiles for GTSRB
+
+0. Ensure you have performed the *Setup* steps in the top-level README for setting up the FINN requirements and environment variables.
+
+1. Run the `download-model.sh` script under the `models` directory to download the pretrained QONNX model. You should have `gtsrb/models/cnv_1w1a_gtsrb.onnx` as a result.
+
+2. Launch the build as follows:
+```SHELL
+# update this according to where you cloned this repo:
+FINN_EXAMPLES=/path/to/finn-examples
+# cd into finn submodule
+cd $FINN_EXAMPLES/build/finn
+# launch the build on the gtsrb folder
+./run-docker.sh build_custom $FINN_EXAMPLES/build/gtsrb
+```
+
+3. The generated outputs will be under `gtsrb/output_<topology>_<board>`. You can find a description of the generated files [here](https://finn-dev.readthedocs.io/en/latest/command_line.html#simple-dataflow-build-mode).
+
+## Where did the ONNX model files come from?
+
+The model is part of the QONNX model zoo and gets directly downloaded from [here](https://github.com/fastmachinelearning/qonnx_model_zoo/tree/feature/gtsrb_cnv/models/GTSRB/Brevitas_CNV1W1A).
diff --git a/build/vgg10-radioml/README.md b/build/vgg10-radioml/README.md
index 17a4524..18df19d 100755
--- a/build/vgg10-radioml/README.md
+++ b/build/vgg10-radioml/README.md
@@ -12,7 +12,7 @@ Due to the 1-dimensional topology in VGG10 we use a specialized build script tha
 
 0. Ensure you have performed the *Setup* steps in the top-level README for setting up the FINN requirements and environment variables.
 
-1. Run the `download_vgg10.sh` script under the `models` directory to download the pretrained VGG10 ONNX model. You should have e.g. `vgg10-radioml/models/radioml_w4a4_small_tidy.onnx` as a result.
+1. Run the `download_vgg10.sh` script under the `models` directory to download the pretrained VGG10 ONNX model. You should have `vgg10-radioml/models/radioml_w4a4_small_tidy.onnx` as a result.
 
 2. Launch the build as follows:
 ```SHELL
@@ -24,7 +24,7 @@ cd $FINN_EXAMPLES/build/finn
 ./run-docker.sh build_custom $FINN_EXAMPLES/build/vgg10
 ```
 
-5. The generated outputs will be under `vgg10-radioml/output_<topology>_<board>`. You can find a description of the generated files [here](https://finn-dev.readthedocs.io/en/latest/command_line.html#simple-dataflow-build-mode).
+3. The generated outputs will be under `vgg10-radioml/output_<topology>_<board>`. You can find a description of the generated files [here](https://finn-dev.readthedocs.io/en/latest/command_line.html#simple-dataflow-build-mode).
 
 ## Where did the ONNX model files come from?
 
diff --git a/finn_examples/notebooks/6_traffic_sign_recognition_gtsrb.ipynb b/finn_examples/notebooks/7_traffic_sign_recognition_gtsrb.ipynb
similarity index 100%
rename from finn_examples/notebooks/6_traffic_sign_recognition_gtsrb.ipynb
rename to finn_examples/notebooks/7_traffic_sign_recognition_gtsrb.ipynb