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jasper-lu
/
temp_markup

Transformers
PyTorch
English
markuplm
Model card Files Files and versions
xet
Community

Instructions to use jasper-lu/temp_markup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use jasper-lu/temp_markup with Transformers:

    # Load model directly
    from transformers import AutoProcessor, MarkupLMForPretraining
    
    processor = AutoProcessor.from_pretrained("jasper-lu/temp_markup")
    model = MarkupLMForPretraining.from_pretrained("jasper-lu/temp_markup")
  • Notebooks
  • Google Colab
  • Kaggle
temp_markup
754 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 3 commits
Jasper Lu
add requirements
39b89b2 over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    887 Bytes
    Add initial over 2 years ago
  • added_tokens.json
    55 Bytes
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  • config.json
    811 Bytes
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  • handler.py
    1.19 kB
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  • merges.txt
    456 kB
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  • preprocessor_config.json
    100 Bytes
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  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    750 MB
    xet
    Add initial over 2 years ago
  • requirements.txt
    323 Bytes
    add requirements over 2 years ago
  • special_tokens_map.json
    280 Bytes
    Add initial over 2 years ago
  • test_handler.py
    211 Bytes
    Add initial over 2 years ago
  • tokenizer.json
    2.11 MB
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  • tokenizer_config.json
    5.5 kB
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  • vocab.json
    798 kB
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