Instructions to use mila-intel/ProtST-esm1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mila-intel/ProtST-esm1b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="mila-intel/ProtST-esm1b", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mila-intel/ProtST-esm1b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mila-intel/ProtST-esm1b: direct link, hf CLI and curl.
- Browser
- Download file 1.53 GB
-
https://huggingface.co/mila-intel/ProtST-esm1b/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mila-intel/ProtST-esm1b/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mila-intel/ProtST-esm1b/resolve/main/pytorch_model.bin
1.53 GB
- Xet hash:
- 23718707f78c3f438dedf4b3b89e0fc98821dcd4186d3bd74c9044d5133127e9
- Size of remote file:
- 1.53 GB
- SHA256:
- c28e06b09d10277ef24cccfb72d8189b7125288c01afb661bb8b5dfb432682e1
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