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 training_args.bin from mgh6/esm_cluster: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/mgh6/esm_cluster/resolve/main/training_args.bin
- Command line
-
hf download hf://mgh6/esm_cluster/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/mgh6/esm_cluster/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 2198891288a2565539d8758a69d92c17d4ad943ff622073725282ff64f5d7ca8
- Size of remote file:
- 3.96 kB
- SHA256:
- a9fb84b2474bbd351af3bd0edd9cb5a43c4589a05ac83683f8c46bee22e19d87
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