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ivelin
/
donut-refexp-combined-v1

Visual Question Answering
Transformers
PyTorch
English
vision-encoder-decoder
image-text-to-text
ui refexp
Model card Files Files and versions
xet
Community
4

Instructions to use ivelin/donut-refexp-combined-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ivelin/donut-refexp-combined-v1 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("visual-question-answering", model="ivelin/donut-refexp-combined-v1")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForImageTextToText
    
    tokenizer = AutoTokenizer.from_pretrained("ivelin/donut-refexp-combined-v1")
    model = AutoModelForImageTextToText.from_pretrained("ivelin/donut-refexp-combined-v1")
  • Notebooks
  • Google Colab
  • Kaggle
donut-refexp-combined-v1
815 MB
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  • 1 contributor
History: 326 commits
ivelin's picture
ivelin
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  • .gitattributes
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  • README.md
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  • added_tokens.json
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  • config.json
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  • generation_config.json
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  • preprocessor_config.json
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  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    809 MB
    xet
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  • sentencepiece.bpe.model
    1.3 MB
    xet
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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