Instructions to use facebook/esmfold_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/esmfold_v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, EsmForProteinFolding tokenizer = AutoTokenizer.from_pretrained("facebook/esmfold_v1") model = EsmForProteinFolding.from_pretrained("facebook/esmfold_v1") - Notebooks
- Google Colab
- Kaggle
ESMFold
ESMFold is a state-of-the-art end-to-end protein folding model based on an ESM-2 backbone. It does not require any lookup or MSA step, and therefore does not require any external databases to be present in order to make predictions. As a result, inference time is very significantly faster than AlphaFold2. For details on the model architecture and training, please refer to the accompanying paper.
If you're interested in using ESMFold in practice, please check out the associated tutorial notebook.
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