Instructions to use multimolecule/bpnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/bpnet with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/bpnet") model = AutoModel.from_pretrained("multimolecule/bpnet") inputs = tokenizer("ACTCCCCTGCCCTCAACAAGATGTTTTGCCAACTGGCCAAGACCTGCCCTGTGCAGCTGTGGGTTGATTCCACACCCCCGCCCGGCACCCGCGTCCGCGCCATGGCCATCTACAAGCAGTCACAGCACATGACGGAGGTTGTGAGGCGCTGCCCCCACCATGAGCGCTGCTCAGATAGCGATGG", return_tensors="pt") outputs = model(**inputs) embeddings = outputs.last_hidden_state - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b087d1b0365b2919d0bff9e54a657fa51a11a685898c527779896e18fd21685c
- Size of remote file:
- 534 kB
- SHA256:
- e29fb801c1b65e77d78706cb82b0ef2f2def848ce7de3495d4d85195d203ca22
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