Transformers
Safetensors
English
esmfold2
biology
esm
protein
protein-structure-prediction
structure-prediction
protein-design
3d-structure
confidence-estimation
molecular-dynamics
Instructions to use biohub/ESMFold2-Experimental-Fast-base300M-step250k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use biohub/ESMFold2-Experimental-Fast-base300M-step250k with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("biohub/ESMFold2-Experimental-Fast-base300M-step250k") model = AutoModel.from_pretrained("biohub/ESMFold2-Experimental-Fast-base300M-step250k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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hf(esmfold2): patch config.json — type '<unset>' -> 'experimental'
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