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mwesner
/
layoutlmv2-cord

Token Classification
Transformers
PyTorch
layoutlmv2
Model card Files Files and versions
xet
Community
1

Instructions to use mwesner/layoutlmv2-cord with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mwesner/layoutlmv2-cord with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="mwesner/layoutlmv2-cord")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForTokenClassification
    
    processor = AutoProcessor.from_pretrained("mwesner/layoutlmv2-cord")
    model = AutoModelForTokenClassification.from_pretrained("mwesner/layoutlmv2-cord")
  • Notebooks
  • Google Colab
  • Kaggle
layoutlmv2-cord
803 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
mwesner's picture
mwesner
add tokenizer
e1790bc about 4 years ago
  • .gitattributes
    1.18 kB
    initial commit about 4 years ago
  • config.json
    3.71 kB
    add model about 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    802 MB
    xet
    add model about 4 years ago
  • special_tokens_map.json
    112 Bytes
    add tokenizer about 4 years ago
  • tokenizer.json
    466 kB
    add tokenizer about 4 years ago
  • tokenizer_config.json
    590 Bytes
    add tokenizer about 4 years ago
  • vocab.txt
    232 kB
    add tokenizer about 4 years ago