Instructions to use yosshstd/ProTrek_650M_UniRef50_structure_encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use yosshstd/ProTrek_650M_UniRef50_structure_encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yosshstd/ProTrek_650M_UniRef50_structure_encoder") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 05dea8bd56cd391ac7f85acbed092e304c75c549c1c1b9ad3f659f8545e661fa
- Size of remote file:
- 593 MB
- SHA256:
- bd02d5816b7a9eca05906fb54e121fd0ea574c655d12950b571217f8699ac926
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