Instructions to use yangheng/mrnafm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use yangheng/mrnafm with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("yangheng/mrnafm") model = AutoModel.from_pretrained("yangheng/mrnafm") inputs = tokenizer("CTGAAAGCGGCCCACGCGGACTGACGGGCGGGGG", return_tensors="pt") outputs = model(**inputs) embeddings = outputs.last_hidden_stateimport multimolecule from transformers import pipeline predictor = pipeline("fill-mask", model="yangheng/mrnafm") output = predictor("CTG<mask>AAGCGGCCCACGCGGACTGACGGGCGGGGG") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3079e44530ff70775dc7be29c474ba95d911dd78f783fb3cc4445dffbe1f6e8b
- Size of remote file:
- 964 MB
- SHA256:
- 2c1d05f5357820e0d46c121b273faef93bd855bdde2eb6d071cc437b92ff38fe
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