Instructions to use multimolecule/ufold with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/ufold with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/ufold") model = AutoModel.from_pretrained("multimolecule/ufold") 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/ufold") output = predictor("UAGCUUAUCAGACUGAUGUUGA") print(output["secondary_structure"]) - Notebooks
- Google Colab
- Kaggle
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README.md
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## Disclaimer
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This is an UNOFFICIAL implementation of [UFold: fast and accurate RNA secondary structure prediction with deep learning](https://doi.org/10.1093/nar/gkab1074) by Laiyi Fu, Yingxin Cao,
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The OFFICIAL repository of UFold is at [uci-cbcl/UFold](https://github.com/uci-cbcl/UFold).
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## Disclaimer
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This is an UNOFFICIAL implementation of [UFold: fast and accurate RNA secondary structure prediction with deep learning](https://doi.org/10.1093/nar/gkab1074) by Laiyi Fu, Yingxin Cao, et al.
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The OFFICIAL repository of UFold is at [uci-cbcl/UFold](https://github.com/uci-cbcl/UFold).
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