| --- |
| license: other |
| license_name: cc-by-nc-4.0 |
| license_link: https://creativecommons.org/licenses/by-nc/4.0/legalcode |
| tags: |
| - enzyme |
| - protein |
| - biology |
| - ec-prediction |
| - multimodal |
| - contrastive-learning |
| language: |
| - en |
| pipeline_tag: feature-extraction |
| --- |
| |
| # RAMER |
|
|
| This Hugging Face repository stores the official resources for **RAMER** (reaction-aware multimodal enzyme function representation model). |
|
|
| ## What is stored in this repository |
|
|
| The repository mainly includes three resource groups: |
|
|
| - `model/` |
| Model weights and tokenizer/config files required for RAMER inference and training reproduction. |
|
|
| - `data/` |
| Benchmark and evaluation data (for example, test CSV/JSON files and related resources used in EC prediction workflows). |
|
|
| - `Background_library/` |
| Background embedding/index resources and dictionary files used by zero-shot retrieval pipelines (e.g., EC label dictionaries and background H5 files). |
|
|
| ## Intended usage |
|
|
| These files are intended for: |
|
|
| - Zero-shot EC function prediction (`top1` and `max-separation`) |
| - Enzyme/non-enzyme binary classification based on RAMER embeddings |
| - Training/inference reproduction using the released scripts |
|
|
| ## Deployment / pipeline reference |
|
|
| For end-to-end scripts, deployment examples, and pipeline details, please refer to the GitHub organization: |
|
|
| - [Ming-Ni-Group on GitHub](https://github.com/Ming-Ni-Group) |
|
|
| And the project repository: |
|
|
| - [Ming-Ni-Group/RAMER](https://github.com/Ming-Ni-Group/RAMER.git) |
|
|
| ## Notes |
|
|
| - This repository is primarily a resource host (weights + data + background library). |
| - Runtime scripts and workflow orchestration are maintained in the GitHub code repository. |
|
|
| ## License |
|
|
| The source code and model weights in this repository are licensed under the [Creative Commons Attribution-NonCommercial 4.0 International License](https://creativecommons.org/licenses/by-nc/4.0/legalcode) (CC BY-NC 4.0). See `LICENSE` for the full text. |
|
|
| Third-party base models (ProtT5, MolT5, GearNet) retain their original licenses. See `THIRD_PARTY_MODELS.md` for details. |
|
|
