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TeeA
/
DONUT-ViChart

Visual Question Answering
Transformers
Safetensors
Vietnamese
vision-encoder-decoder
image-text-to-text
Model card Files Files and versions
xet
Community

Instructions to use TeeA/DONUT-ViChart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use TeeA/DONUT-ViChart with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("visual-question-answering", model="TeeA/DONUT-ViChart")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForImageTextToText
    
    tokenizer = AutoTokenizer.from_pretrained("TeeA/DONUT-ViChart")
    model = AutoModelForImageTextToText.from_pretrained("TeeA/DONUT-ViChart")
  • Notebooks
  • Google Colab
  • Kaggle
DONUT-ViChart
747 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 144 commits
TeeA's picture
TeeA
Config
d0c721b verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    167 Bytes
    Training in progress, epoch 1 almost 2 years ago
  • ViChart-demo.png
    48.2 kB
    Upload ViChart-demo.png over 2 years ago
  • added_tokens.json
    200 Bytes
    Config almost 2 years ago
  • config.json
    4.89 kB
    Training in progress, epoch 0 almost 2 years ago
  • dict.txt
    360 kB
    Config over 2 years ago
  • generation_config.json
    181 Bytes
    Training in progress, epoch 1 almost 2 years ago
  • model.safetensors
    737 MB
    xet
    Training in progress, epoch 10 almost 2 years ago
  • preprocessor_config.json
    756 Bytes
    Config almost 2 years ago
  • sentencepiece.bpe.model
    5.07 MB
    xet
    Config almost 2 years ago
  • special_tokens_map.json
    279 Bytes
    Config almost 2 years ago
  • tokenizer.json
    4.01 MB
    Config almost 2 years ago
  • tokenizer_config.json
    2.81 kB
    Config almost 2 years ago