Instructions to use multimolecule/progen2-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/progen2-medium with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/progen2-medium") model = AutoModel.from_pretrained("multimolecule/progen2-medium") inputs = tokenizer("MANLGCWMLVLFVATWSDLGLCKKRPKPGGWNTGGSRYPGQGSPGGNRYPPQGGGGWGQPHGGGWGQPHGGGWGQPHGGGWGQPHGGGWGQGGGTHSQWNKPSKPKTNMKHMAGAAAAGAVVGGLGGYMLGSAMSRPIIHFGSDYEDRYYRENMHRYPNQVYYRPMDEYSNQNNFVHDCVNITIKQHTVTTTTKGENFTETDVKMMERVVEQMCITQYERESQAYYQRGSSMV", return_tensors="pt") outputs = model(**inputs) embeddings = outputs.last_hidden_state - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7e3a7013ea98f8be9d66b366281898170709d25a89e40d0d2436d3dbc4ea6383
- Size of remote file:
- 3.06 GB
- SHA256:
- 25e44200179ed0632f912da891a46454c553051ff29bae21f6caea0eb021ff7f
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