Instructions to use multimolecule/rnafm-ss with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/rnafm-ss with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/rnafm-ss") model = AutoModel.from_pretrained("multimolecule/rnafm-ss") inputs = tokenizer("UAGCUUAUCAGACUGAUGUUGA", return_tensors="pt") outputs = model(**inputs) embeddings = outputs.last_hidden_stateimport multimolecule from transformers import pipeline predictor = pipeline("rna-secondary-structure", model="multimolecule/rnafm-ss") output = predictor("UAGCUUAUCAGACUGAUGUUGA") print(output["secondary_structure"]) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f4b0d57ff997288cc6bdbc46e27d11e90053431afac1e494da461831ac4de0c
- Size of remote file:
- 408 MB
- SHA256:
- b4055476236642138e78761bd3fefadf2e7f7cc882bf5676f2a151ec6380ca2b
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