Instructions to use ChatterjeeLab/MetaLATTE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChatterjeeLab/MetaLATTE with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ChatterjeeLab/MetaLATTE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download __init__.py from ChatterjeeLab/MetaLATTE: direct link, hf CLI and curl.
- Browser
- Download file 241 Bytes
-
https://huggingface.co/ChatterjeeLab/MetaLATTE/resolve/main/__init__.py
- Command line
-
hf download hf://ChatterjeeLab/MetaLATTE/__init__.py
-
curl -L -o __init__.py https://huggingface.co/ChatterjeeLab/MetaLATTE/resolve/main/__init__.py
241 Bytes
| from transformers import AutoConfig, AutoModel | |
| from .configuration import MetaLATTEConfig | |
| from .model import MultitaskProteinModel | |
| AutoConfig.register("metalatte", MetaLATTEConfig) | |
| AutoModel.register(MetaLATTEConfig, MultitaskProteinModel) |