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-base600M-step750k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use biohub/ESMFold2-Experimental-Fast-base600M-step750k with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("biohub/ESMFold2-Experimental-Fast-base600M-step750k") model = AutoModel.from_pretrained("biohub/ESMFold2-Experimental-Fast-base600M-step750k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from biohub/ESMFold2-Experimental-Fast-base600M-step750k: direct link, hf CLI and curl.
- Browser
- Download file 685 MB
-
https://huggingface.co/biohub/ESMFold2-Experimental-Fast-base600M-step750k/resolve/51b3b03e0d8f8dd6f53bbc1c65048a7faaf9f200/model.safetensors
- Command line
-
hf download hf://biohub/ESMFold2-Experimental-Fast-base600M-step750k@51b3b03e0d8f8dd6f53bbc1c65048a7faaf9f200/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/biohub/ESMFold2-Experimental-Fast-base600M-step750k/resolve/51b3b03e0d8f8dd6f53bbc1c65048a7faaf9f200/model.safetensors
685 MB
- Xet hash:
- 4a9c6a35543700ed1f1cc4634fe75fd22232aec1e76a23cc18ccc6371a24c131
- Size of remote file:
- 685 MB
- SHA256:
- 0d2f84c4b20553e003fe042a1a04f2e81853082f7c666bc1371ab752bab40a07
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