Instructions to use multimolecule/calm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/calm with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/calm") model = AutoModel.from_pretrained("multimolecule/calm") inputs = tokenizer("ACTCCCCTGCCCTCAAAGATGTTTTGCCAACTGGCCAAGACCTGCCCTGTGCAGCTGTGGGTTGATTCCACACCCCCGCCCGGCACCCGCGTCCGCGCCATGGCCATCTACAAGCAGTCACAGCACATGACGGAGGTTGTGAGGCGCTGCCCCCACCATGAGCGCTGCTCAGATAGCGATG", return_tensors="pt") outputs = model(**inputs) embeddings = outputs.last_hidden_stateimport multimolecule from transformers import pipeline predictor = pipeline("fill-mask", model="multimolecule/calm") output = predictor("ACTCCCCTGCCCTCA<mask>AGATGTTTTGCCAACTGGCCAAGACCTGCCCTGTGCAGCTGTGGGTTGATTCCACACCCCCGCCCGGCACCCGCGTCCGCGCCATGGCCATCTACAAGCAGTCACAGCACATGACGGAGGTTGTGAGGCGCTGCCCCCACCATGAGCGCTGCTCAGATAGCGATG") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b96aac5aece4a861d360bebda1bfeff7fcea791d9d1f6ccb13186e9313a8430c
- Size of remote file:
- 343 MB
- SHA256:
- f7d03c53cedf74d4d71c9d5a8ee7ff9a8c69246b2485b66cbbc84c156ac434ac
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