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nafiz09
/
docvqa

Document Question Answering
Transformers
PyTorch
vision-encoder-decoder
image-text-to-text
donut
image-to-text
vision
Model card Files Files and versions
xet
Community
1

Instructions to use nafiz09/docvqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use nafiz09/docvqa with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("document-question-answering", model="nafiz09/docvqa")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForMultimodalLM
    
    tokenizer = AutoTokenizer.from_pretrained("nafiz09/docvqa")
    model = AutoModelForMultimodalLM.from_pretrained("nafiz09/docvqa")
  • Notebooks
  • Google Colab
  • Kaggle
docvqa
809 MB
Ctrl+K
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  • 1 contributor
History: 33 commits
nafiz09's picture
nafiz09
Upload 11 files
8a87927 verified over 2 years ago
  • .gitattributes
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  • .gitignore
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  • README.md
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  • added_tokens.json
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  • config.json
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  • preprocessor_config.json
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  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    803 MB
    xet
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  • sentencepiece.bpe.model
    1.3 MB
    xet
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  • special_tokens_map.json
    478 Bytes
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  • tokenizer.json
    4.01 MB
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  • tokenizer_config.json
    535 Bytes
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