diff --git a/.github/workflows/publish-book.yml b/.github/workflows/publish-book.yml index ba81c24..0a12f3b 100644 --- a/.github/workflows/publish-book.yml +++ b/.github/workflows/publish-book.yml @@ -21,7 +21,7 @@ jobs: python -m pip install --upgrade pip python -m pip install -e . python -m pip install .[docs] - pip install jupyter-book sphinxcontrib-mermaid + pip install jupyter-book sphinxcontrib-mermaid numpydoc - name: Build the book run: | diff --git a/README.md b/README.md index dc9a70f..df982dc 100644 --- a/README.md +++ b/README.md @@ -1,8 +1,8 @@ # CEBRA-Lens -## A python library for mechanistic interpretability of CEBRA models +cebra-lens - cebra-lens +A python library for mechanistic interpretability of CEBRA models **CEBRA-Lens** is a Python library for analyzing and interpreting neural representations learned by models trained with [CEBRA](https://github.com/AdaptiveMotorControlLab/cebra). It provides tools for mechanistic interpretability, allowing users to probe, visualize, and understand the structure of learned embeddings. The library is designed to support in-depth analysis of representational geometry, feature selectivity, and latent space dynamics in neuroscience and beyond. 👋 We welcome contributions and will continue to expand the library in the coming years. @@ -18,13 +18,13 @@ conda create -n CEBRAlens python=3.12 conda activate CEBRAlens conda install -c conda-forge pytables==3.8.0 -# install PyTorch with your desired CUDA version (or for CPU only)- check their website: https://pytorch.org/get-started/locally/ +# install PyTorch with your desired CUDA version - check their website: https://pytorch.org/get-started/locally/ # example: GPU version of pytorch for CUDA 11.3 conda install pytorch cudatoolkit=11.3 -c pytorch # install CEBRA and CEBRA-lens pip install --pre 'cebra[datasets,demos]' -pip install -- cebra_lens +pip install --pre cebra_lens ``` ## 🦓🔍 Analysis Methods @@ -65,7 +65,9 @@ These analyses quantify the change in the distance calculated per layer in a mod - inter-class distance - inter-repetition distance (only relevant if the model was trained on a dataset where there is repeating stimuli) -analysis +analysis + + # Demo diff --git a/docs/docs/images/abstractfig.png b/docs/docs/images/abstractfig.png deleted file mode 100644 index 2bf2925..0000000 Binary files a/docs/docs/images/abstractfig.png and /dev/null differ diff --git a/docs/docs/images/zebra.png b/docs/docs/images/zebra.png deleted file mode 100644 index 8328e76..0000000 Binary files a/docs/docs/images/zebra.png and /dev/null differ