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unsloth
/
embeddinggemma-300m-qat-q4_0-unquantized

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

Instructions to use unsloth/embeddinggemma-300m-qat-q4_0-unquantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use unsloth/embeddinggemma-300m-qat-q4_0-unquantized with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("unsloth/embeddinggemma-300m-qat-q4_0-unquantized")
    
    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
embeddinggemma-300m-qat-q4_0-unquantized
1.27 GB
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  • 1 contributor
History: 3 commits
danielhanchen's picture
danielhanchen
Update README.md
a2f8a2f verified 9 months ago
  • 1_Pooling
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  • 2_Dense
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  • .gitattributes
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  • README.md
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  • added_tokens.json
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  • config.json
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  • config_sentence_transformers.json
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  • generation_config.json
    133 Bytes
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  • model.safetensors
    1.21 GB
    xet
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  • modules.json
    573 Bytes
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  • sentence_bert_config.json
    58 Bytes
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  • special_tokens_map.json
    662 Bytes
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  • tokenizer.json
    33.4 MB
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  • tokenizer.model
    4.69 MB
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  • tokenizer_config.json
    1.16 MB
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