Instructions to use multimolecule/rnaernie with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/rnaernie with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/rnaernie") model = AutoModel.from_pretrained("multimolecule/rnaernie") 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/rnaernie") output = predictor("UAGCUUAUCAG<mask>CUGAUGUUGA") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from multimolecule/rnaernie: direct link, hf CLI and curl.
- Browser
- Download file 347 MB
-
https://huggingface.co/multimolecule/rnaernie/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://multimolecule/rnaernie/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/multimolecule/rnaernie/resolve/main/pytorch_model.bin
347 MB
- Xet hash:
- 3bbded201c23f9d8a9d2e6dbb7b50ff501ea0cc62b2efac1184e04187168a8d5
- Size of remote file:
- 347 MB
- SHA256:
- f47bfb5f67480758467ed281126005eb2bbd22787bae3f33b49879ac77c73b16
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