Instructions to use multimolecule/rinalmo-mega with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/rinalmo-mega with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/rinalmo-mega") model = AutoModel.from_pretrained("multimolecule/rinalmo-mega") 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/rinalmo-mega") output = predictor("UAGCUUAUCAG<mask>CUGAUGUUGA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- adefdfee75ca8a4ac749b9748cbb9ffcde65314b18ab12b9d38aca039f7a33d9
- Size of remote file:
- 592 MB
- SHA256:
- f19c234c7c362e608c09335279123d25edc9d117c307749fbec7a6ed7d44fe25
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