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gbyuvd
/
miniChembed-prototype

Sentence Similarity
sentence-transformers
Safetensors
roberta
chemistry
molecular-similarity
cheminformatics
ssl
smiles
feature-extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use gbyuvd/miniChembed-prototype with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use gbyuvd/miniChembed-prototype with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("gbyuvd/miniChembed-prototype")
    
    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
miniChembed-prototype / examples
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  • 1 contributor
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