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Xiaoman
/
NER-CoNLL2003

Token Classification
Transformers
PyTorch
TensorBoard
bert
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use Xiaoman/NER-CoNLL2003 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Xiaoman/NER-CoNLL2003 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="Xiaoman/NER-CoNLL2003")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("Xiaoman/NER-CoNLL2003")
    model = AutoModelForTokenClassification.from_pretrained("Xiaoman/NER-CoNLL2003")
  • Notebooks
  • Google Colab
  • Kaggle
NER-CoNLL2003
1.34 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
Xiaoman's picture
Xiaoman
add tokenizer
157e5cd about 4 years ago
  • runs
    End of training about 4 years ago
  • .gitattributes
    1.17 kB
    initial commit about 4 years ago
  • .gitignore
    13 Bytes
    Training in progress, step 500 about 4 years ago
  • config.json
    1.02 kB
    add config about 4 years ago
  • pytorch_model.bin
    1.34 GB
    xet
    End of training about 4 years ago
  • special_tokens_map.json
    112 Bytes
    add tokenizer about 4 years ago
  • tokenizer.json
    712 kB
    add tokenizer about 4 years ago
  • tokenizer_config.json
    322 Bytes
    add tokenizer about 4 years ago
  • training_args.bin
    3.25 kB
    xet
    Training in progress, step 500 about 4 years ago
  • vocab.txt
    232 kB
    add tokenizer about 4 years ago