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Ayeshas21
/
sentence-transformers-all-MiniLM-L6-v2-quantized

Sentence Similarity
sentence-transformers
ONNX
bert
quantized
clustering
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use Ayeshas21/sentence-transformers-all-MiniLM-L6-v2-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use Ayeshas21/sentence-transformers-all-MiniLM-L6-v2-quantized with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("Ayeshas21/sentence-transformers-all-MiniLM-L6-v2-quantized")
    
    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
sentence-transformers-all-MiniLM-L6-v2-quantized
113 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
Ayeshas21's picture
Ayeshas21
Upload folder using huggingface_hub
e6fbd97 verified 10 months ago
  • .gitattributes
    1.52 kB
    initial commit 10 months ago
  • README.md
    3.82 kB
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  • config.json
    650 Bytes
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  • model-quant.onnx
    22.9 MB
    xet
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  • model.onnx
    90.4 MB
    xet
    Upload folder using huggingface_hub 10 months ago