Instructions to use multimolecule/rnafm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/rnafm with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/rnafm") model = AutoModel.from_pretrained("multimolecule/rnafm") inputs = tokenizer("UAGCUUAUCAGACUGAUGUUGA", return_tensors="pt") outputs = model(**inputs) embeddings = outputs.last_hidden_stateimport multimolecule from transformers import pipeline predictor = pipeline("fill-mask", model="multimolecule/rnafm") output = predictor("UAGCUUAUCAG<mask>CUGAUGUUGA") - 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 the [Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions](https://doi.org/10.1101/2022.08.06.503062) by Jiayang Chen, Zhihang
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The OFFICIAL repository of RNA-FM is at [ml4bio/RNA-FM](https://github.com/ml4bio/RNA-FM).
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## Disclaimer
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This is an UNOFFICIAL implementation of the [Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions](https://doi.org/10.1101/2022.08.06.503062) by Jiayang Chen, Zhihang Hu, Siqi Sun, et al.
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The OFFICIAL repository of RNA-FM is at [ml4bio/RNA-FM](https://github.com/ml4bio/RNA-FM).
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