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lambdaofgod
/
document_nbow_embedder

Sentence Similarity
sentence-transformers
feature-extraction
Model card Files Files and versions
xet
Community

Instructions to use lambdaofgod/document_nbow_embedder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use lambdaofgod/document_nbow_embedder with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("lambdaofgod/document_nbow_embedder")
    
    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
document_nbow_embedder
1.48 kB
Ctrl+K
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  • 1 contributor
History: 1 commit
lambdaofgod's picture
lambdaofgod
initial commit
9a44ee2 over 3 years ago
  • .gitattributes
    1.48 kB
    initial commit over 3 years ago