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COPA
/
WL-url-text-class

Text Classification
sentence-transformers
PyTorch
setfit
bert
text-embeddings-inference
Model card Files Files and versions
xet
Community
1

Instructions to use COPA/WL-url-text-class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use COPA/WL-url-text-class with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("COPA/WL-url-text-class")
    
    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 COPA/WL-url-text-class with setfit:

    from setfit import SetFitModel
    
    model = SetFitModel.from_pretrained("COPA/WL-url-text-class")
  • Notebooks
  • Google Colab
  • Kaggle
WL-url-text-class
503 MB
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  • 1 contributor
History: 2 commits
yjmsvma's picture
yjmsvma
Add SetFit model
c2c32cc verified almost 2 years ago
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  • .gitattributes
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  • README.md
    1.54 kB
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  • config.json
    751 Bytes
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  • config_sentence_transformers.json
    122 Bytes
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  • model_head.pkl

    Detected Pickle imports (4)

    • "joblib.numpy_pickle.NumpyArrayWrapper",
    • "sklearn.linear_model._logistic.LogisticRegression",
    • "numpy.ndarray",
    • "numpy.dtype"

    How to fix it?

    19.8 kB
    xet
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  • modules.json
    229 Bytes
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  • pytorch_model.bin

    Detected Pickle imports (4)

    • "torch.FloatStorage",
    • "collections.OrderedDict",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.LongStorage"

    What is a pickle import?

    471 MB
    xet
    Add SetFit model almost 2 years ago
  • sentence_bert_config.json
    53 Bytes
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  • special_tokens_map.json
    280 Bytes
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  • tokenizer.json
    17.1 MB
    xet
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  • tokenizer_config.json
    496 Bytes
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  • unigram.json
    14.8 MB
    xet
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