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gubartz
/
st_all_mini_science

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
text-embeddings-inference
Model card Files Files and versions
xet
Community

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

  • Libraries
  • sentence-transformers

    How to use gubartz/st_all_mini_science with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("gubartz/st_all_mini_science")
    
    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
st_all_mini_science
134 MB
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  • 1 contributor
History: 12 commits
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gubartz
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  • .gitattributes
    1.52 kB
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  • README.md
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  • config.json
    680 Bytes
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  • config_sentence_transformers.json
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  • model.safetensors
    133 MB
    xet
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  • modules.json
    349 Bytes
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    695 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    1.43 kB
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  • vocab.txt
    232 kB
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