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RikkaBotan
/
quantized-stable-static-embedding-fast-retrieval-mrl-en

Sentence Similarity
sentence-transformers
English
feature-extraction
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use RikkaBotan/quantized-stable-static-embedding-fast-retrieval-mrl-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use RikkaBotan/quantized-stable-static-embedding-fast-retrieval-mrl-en with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("RikkaBotan/quantized-stable-static-embedding-fast-retrieval-mrl-en")
    
    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
quantized-stable-static-embedding-fast-retrieval-mrl-en
14.7 MB
Ctrl+K
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  • 1 contributor
History: 17 commits
RikkaBotan's picture
RikkaBotan
Update README.md
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  • assets
    Upload SSE_comp_en.png 2 months ago
  • .gitattributes
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  • README.md
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  • SSE_quantize.py
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  • config_sentence_transformers.json
    296 Bytes
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  • embedding.q4_k_m.bin
    7.94 MB
    xet
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  • model_rest.safetensors
    6.36 kB
    xet
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  • modules.json
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  • tokenizer.json
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