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owen99630
/
catexp

Transformers
PyTorch
roberta
Model card Files Files and versions
xet
Community

Instructions to use owen99630/catexp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use owen99630/catexp with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, RobertaForMultiLabelSequenceClassification
    
    tokenizer = AutoTokenizer.from_pretrained("owen99630/catexp")
    model = RobertaForMultiLabelSequenceClassification.from_pretrained("owen99630/catexp")
  • Notebooks
  • Google Colab
  • Kaggle
catexp
503 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
s3766882
update models
b09b21e over 4 years ago
  • .gitattributes
    1.18 kB
    initial commit over 4 years ago
  • config.json
    4.22 kB
    update models over 4 years ago
  • eval_results.txt
    56 Bytes
    add models over 4 years ago
  • merges.txt
    456 kB
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  • model_args.json
    2.41 kB
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  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    501 MB
    xet
    update models over 4 years ago
  • special_tokens_map.json
    772 Bytes
    add models over 4 years ago
  • tokenizer_config.json
    1.33 kB
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  • training_args.bin
    2.99 kB
    xet
    update models over 4 years ago
  • vocab.json
    899 kB
    add models over 4 years ago