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scales-okn
/
ner-entry-date-section

Token Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
Model card Files Files and versions
xet
Community

Instructions to use scales-okn/ner-entry-date-section with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use scales-okn/ner-entry-date-section with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="scales-okn/ner-entry-date-section")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("scales-okn/ner-entry-date-section")
    model = AutoModelForTokenClassification.from_pretrained("scales-okn/ner-entry-date-section", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
ner-entry-date-section
Ctrl+K
Ctrl+K
  • 2 contributors
History: 5 commits
adamrpah's picture
adamrpah
Document GPL-3.0 public release
b99ff1a verified 15 days ago
  • .gitattributes
    1.17 kB
    initial commit about 4 years ago
  • .gitignore
    13 Bytes
    End of training about 4 years ago
  • README.md
    2.42 kB
    Document GPL-3.0 public release 15 days ago
  • added_tokens.json
    18 Bytes
    End of training about 4 years ago
  • config.json
    1.09 kB
    End of training about 4 years ago
  • pytorch_model.bin
    1.74 GB
    xet
    End of training about 4 years ago
  • special_tokens_map.json
    156 Bytes
    End of training about 4 years ago
  • spm.model
    2.46 MB
    xet
    End of training about 4 years ago
  • tokenizer.json
    8.65 MB
    End of training about 4 years ago
  • tokenizer_config.json
    375 Bytes
    End of training about 4 years ago
  • training_args.bin
    3.25 kB
    xet
    End of training about 4 years ago