| license: other | |
| license_name: enzymecage-research-license | |
| license_link: https://huggingface.co/GENTEL-Lab/EnzymeCAGE/blob/main/LICENSE | |
| tags: | |
| - enzyme-retrieval | |
| - geometric-deep-learning | |
| - protein | |
| # EnzymeCAGE pretrained checkpoints | |
| Pretrained epoch 19 checkpoints for [EnzymeCAGE](https://github.com/GENTEL-lab/EnzymeCAGE), *A Geometric Foundation Model for Enzyme Retrieval with Evolutionary Insights* (Nature Catalysis, 2026). These are PyTorch state dictionaries for the repository's model code, with seeds 40–44 under `pretrain/`. The repository's demo and evaluation configs use `pretrain/seed_42/epoch_19.pth`. | |
| ## Download and run | |
| From the EnzymeCAGE repository root: | |
| ```bash | |
| pip install -U huggingface_hub | |
| hf download GENTEL-Lab/EnzymeCAGE pretrain/seed_42/epoch_19.pth --local-dir checkpoints | |
| python infer.py --config config/demo/infer.yaml | |
| ``` | |
| To download all five seeds instead: | |
| ```bash | |
| hf download GENTEL-Lab/EnzymeCAGE --include "pretrain/*/epoch_19.pth" --local-dir checkpoints | |
| ``` | |
| The dataset and generated features needed for inference are described in the [GitHub README](https://github.com/GENTEL-lab/EnzymeCAGE#dataset). A file list with sizes and SHA-256 checksums is in [`checkpoint_manifest.json`](checkpoint_manifest.json). The original `checkpoints.zip` is also linked from the GitHub README. | |
| ## License | |
| See [LICENSE](LICENSE) for the full terms, including restrictions on commercial use and drug development or discovery. | |