Instructions to use multimolecule/chrombpnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/chrombpnet with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/chrombpnet") model = AutoModel.from_pretrained("multimolecule/chrombpnet") inputs = tokenizer("ACTCCCCTGCCCTCAACAAGATGTTTTGCCAACTGGCCAAGACCTGCCCTGTGCAGCTGTGGGTTGATTCCACACCCCCGCCCGGCACCCGCGTCCGCGCCATGGCCATCTACAAGCAGTCACAGCACATGACGGAGGTTGTGAGGCGCTGCCCCCACCATGAGCGCTGCTCAGATAGCGATGG", return_tensors="pt") outputs = model(**inputs) embeddings = outputs.last_hidden_state - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fb2ded5064851bb22d57bb264f621aba6c9b4ded0f3c24f811527841b51fc1b5
- Size of remote file:
- 26.5 MB
- SHA256:
- 75b151148da48ada81c20a54915db2bc64c2c07f5051ebe16f2292b7cc38404e
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