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AHMED36
/
LILT_DocLayNet_Large

Token Classification
Transformers
PyTorch
lilt
Generated from Trainer
Model card Files Files and versions
xet
Community

Instructions to use AHMED36/LILT_DocLayNet_Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use AHMED36/LILT_DocLayNet_Large with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="AHMED36/LILT_DocLayNet_Large")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("AHMED36/LILT_DocLayNet_Large")
    model = AutoModelForTokenClassification.from_pretrained("AHMED36/LILT_DocLayNet_Large", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle

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Preview of files found in this repository
  • config.json
    1.27 kB
    Training in progress, step 5000, checkpoint about 3 years ago
  • optimizer.pt
    2.27 GB
    xet
    Training in progress, step 5000, checkpoint about 3 years ago
  • pytorch_model.bin
    1.13 GB
    xet
    Training in progress, step 5000, checkpoint about 3 years ago
  • rng_state.pth
    14.6 kB
    xet
    Training in progress, step 5000, checkpoint about 3 years ago
  • scheduler.pt
    627 Bytes
    xet
    Training in progress, step 5000, checkpoint about 3 years ago
  • special_tokens_map.json
    280 Bytes
    Training in progress, step 5000, checkpoint about 3 years ago
  • tokenizer.json
    17.1 MB
    xet
    Training in progress, step 5000, checkpoint about 3 years ago
  • tokenizer_config.json
    418 Bytes
    Training in progress, step 5000, checkpoint about 3 years ago
  • trainer_state.json
    3.61 kB
    Training in progress, step 5000, checkpoint about 3 years ago
  • training_args.bin
    4.22 kB
    xet
    Training in progress, step 5000, checkpoint about 3 years ago