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bengid
/
pii-redaction-deberta-base

Token Classification
Transformers
Safetensors
English
deberta-v2
pii
ner
deberta
privacy
named-entity-recognition
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use bengid/pii-redaction-deberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use bengid/pii-redaction-deberta-base with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="bengid/pii-redaction-deberta-base")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("bengid/pii-redaction-deberta-base")
    model = AutoModelForTokenClassification.from_pretrained("bengid/pii-redaction-deberta-base")
  • Notebooks
  • Google Colab
  • Kaggle
pii-redaction-deberta-base
744 MB
Ctrl+K
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  • 1 contributor
History: 9 commits
bengid's picture
bengid
Upload README.md with huggingface_hub
b248dde verified 19 days ago
  • .gitattributes
    1.52 kB
    initial commit about 1 month ago
  • README.md
    8.18 kB
    Upload README.md with huggingface_hub 19 days ago
  • config.json
    3.32 kB
    Upload DebertaV2ForTokenClassification about 1 month ago
  • model.safetensors
    736 MB
    xet
    Upload DebertaV2ForTokenClassification about 1 month ago
  • tokenizer.json
    8.34 MB
    Upload tokenizer about 1 month ago
  • tokenizer_config.json
    537 Bytes
    Upload tokenizer about 1 month ago