Instructions to use multimolecule/rnabert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/rnabert with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/rnabert") model = AutoModel.from_pretrained("multimolecule/rnabert") 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/rnabert") 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 [Informative RNA-base embedding for functional RNA clustering and structural alignment](https://doi.org/10.1093/nargab/lqac012) by Manato Akiyama
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The OFFICIAL repository of RNABERT is at [mana438/RNABERT](https://github.com/mana438/RNABERT).
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## Disclaimer
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This is an UNOFFICIAL implementation of the [Informative RNA-base embedding for functional RNA clustering and structural alignment](https://doi.org/10.1093/nargab/lqac012) by Manato Akiyama, et al.
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The OFFICIAL repository of RNABERT is at [mana438/RNABERT](https://github.com/mana438/RNABERT).
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