Instructions to use multimolecule/esmc-300m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/esmc-300m with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/esmc-300m") model = AutoModel.from_pretrained("multimolecule/esmc-300m") inputs = tokenizer("Paris is the A of France.", return_tensors="pt") outputs = model(**inputs) embeddings = outputs.last_hidden_stateimport multimolecule from transformers import pipeline predictor = pipeline("fill-mask", model="multimolecule/esmc-300m") output = predictor("Paris is the <mask> of France.") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0d2a8412bd0b1d99c6ccdd3f14196470626ce2baa37382046d0e646afaf41f8a
- Size of remote file:
- 1.33 GB
- SHA256:
- 4c15c5a334b6362392418cf2302365c7f71953f86c4709c99b767497b501072a
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