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griffin
/
clinical-summary-fact-corrector

Transformers
PyTorch
bart
text2text-generation
Model card Files Files and versions
xet
Community
1

Instructions to use griffin/clinical-summary-fact-corrector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use griffin/clinical-summary-fact-corrector with Transformers:

    # Load model directly
    from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
    
    tokenizer = AutoTokenizer.from_pretrained("griffin/clinical-summary-fact-corrector")
    model = AutoModelForSeq2SeqLM.from_pretrained("griffin/clinical-summary-fact-corrector")
  • Notebooks
  • Google Colab
  • Kaggle
clinical-summary-fact-corrector
561 MB
Ctrl+K
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  • 2 contributors
History: 3 commits
griffin's picture
griffin
Update README.md
903f6f8 over 3 years ago
  • .gitattributes
    1.38 kB
    initial commit over 3 years ago
  • LICENSE
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  • README.md
    427 Bytes
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  • added_tokens.json
    1.9 kB
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  • config.json
    1.74 kB
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  • merges.txt
    456 kB
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    558 MB
    xet
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  • special_tokens_map.json
    754 Bytes
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  • tokenizer.json
    1.37 MB
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  • tokenizer_config.json
    378 Bytes
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  • vocab.json
    798 kB
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