Instructions to use mgh6/esm_cluster with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mgh6/esm_cluster with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mgh6/esm_cluster")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mgh6/esm_cluster") model = AutoModelForMaskedLM.from_pretrained("mgh6/esm_cluster", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from mgh6/esm_cluster: direct link, hf CLI and curl.
- Browser
- Download file 595 MB
-
https://huggingface.co/mgh6/esm_cluster/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://mgh6/esm_cluster/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/mgh6/esm_cluster/resolve/main/pytorch_model.bin
595 MB
- Xet hash:
- cf794c72fd92733fb628c5aa0f8e4aff1dc6dda6affade09a6445be1547162c5
- Size of remote file:
- 595 MB
- SHA256:
- 431e549265cc485f1bbdd7e631f94dafdc0ed7218aa61c15c5291e92705b6ce4
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