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jncraton
/
gte-tiny-ct2-int8

Sentence Similarity
sentence-transformers
Transformers
feature-extraction
mteb
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use jncraton/gte-tiny-ct2-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use jncraton/gte-tiny-ct2-int8 with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("jncraton/gte-tiny-ct2-int8")
    
    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]
  • Transformers

    How to use jncraton/gte-tiny-ct2-int8 with Transformers:

    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("jncraton/gte-tiny-ct2-int8", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
gte-tiny-ct2-int8
24.8 MB
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  • 1 contributor
History: 3 commits
jncraton's picture
jncraton
Upload vocabulary.txt
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  • .gitattributes
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  • README.md
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  • config.json
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  • model.bin
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    xet
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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  • vocab.txt
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  • vocabulary.json
    390 kB
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  • vocabulary.txt
    232 kB
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