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MDDDDR
/
bert_base_uncased_NER

Token Classification
Transformers
Safetensors
English
bert
BERT
medical
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use MDDDDR/bert_base_uncased_NER with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="MDDDDR/bert_base_uncased_NER")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("MDDDDR/bert_base_uncased_NER")
    model = AutoModelForTokenClassification.from_pretrained("MDDDDR/bert_base_uncased_NER")
  • Notebooks
  • Google Colab
  • Kaggle
bert_base_uncased_NER
437 MB
Ctrl+K
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  • 1 contributor
History: 10 commits
MDDDDR's picture
MDDDDR
Update README.md
ddfa4cf verified about 2 years ago
  • .gitattributes
    1.52 kB
    initial commit about 2 years ago
  • README.md
    1.53 kB
    Update README.md about 2 years ago
  • config.json
    817 Bytes
    Update config.json about 2 years ago
  • model.safetensors
    436 MB
    xet
    Upload BertForTokenClassification about 2 years ago
  • special_tokens_map.json
    125 Bytes
    Upload tokenizer about 2 years ago
  • tokenizer.json
    711 kB
    Upload tokenizer about 2 years ago
  • tokenizer_config.json
    1.19 kB
    Upload tokenizer about 2 years ago
  • vocab.txt
    232 kB
    Upload tokenizer about 2 years ago