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tkuye
/
setfit-jdc

Text Classification
sentence-transformers
PyTorch
setfit
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use tkuye/setfit-jdc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use tkuye/setfit-jdc with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("tkuye/setfit-jdc")
    
    sentences = [
        "The weather is lovely today.",
        "It's so sunny outside!",
        "He drove to the stadium."
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [3, 3]
  • setfit

    How to use tkuye/setfit-jdc with setfit:

    from setfit import SetFitModel
    
    model = SetFitModel.from_pretrained("tkuye/setfit-jdc")
  • Notebooks
  • Google Colab
  • Kaggle
setfit-jdc
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
tkuye's picture
tkuye
Upload ./ with huggingface_hub
e7793c6 about 3 years ago
  • 1_Pooling
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  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • README.md
    1.51 kB
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  • config.json
    720 Bytes
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  • config_sentence_transformers.json
    116 Bytes
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  • model_head.pkl
    28.3 kB
    xet
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  • modules.json
    349 Bytes
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  • pytorch_model.bin
    90.9 MB
    xet
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  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    125 Bytes
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  • tokenizer.json
    712 kB
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  • tokenizer_config.json
    564 Bytes
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  • vocab.txt
    232 kB
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