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screenpipe
/
pii-redactor

Token Classification
Transformers
ONNX
xlm-roberta
pii
privacy
redaction
accessibility-tree
ocr
computer-use
agentic
screen-capture
screenpipe
Model card Files Files and versions
xet
Community

Instructions to use screenpipe/pii-redactor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use screenpipe/pii-redactor with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("token-classification", model="screenpipe/pii-redactor")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForTokenClassification
    
    tokenizer = AutoTokenizer.from_pretrained("screenpipe/pii-redactor")
    model = AutoModelForTokenClassification.from_pretrained("screenpipe/pii-redactor")
  • Notebooks
  • Google Colab
  • Kaggle
pii-redactor / web
295 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 5 commits
louis030195's picture
louis030195
web demo (transformers.js layout): web/onnx/model_quantized.onnx
ffccb6a verified 25 days ago
  • onnx
    web demo (transformers.js layout): web/onnx/model_quantized.onnx 25 days ago
  • config.json
    2.17 kB
    web demo (transformers.js layout): web/config.json 25 days ago
  • special_tokens_map.json
    964 Bytes
    web demo (transformers.js layout): web/special_tokens_map.json 25 days ago
  • tokenizer.json
    17.1 MB
    xet
    web demo (transformers.js layout): web/tokenizer.json 25 days ago
  • tokenizer_config.json
    1.29 kB
    web demo (transformers.js layout): web/tokenizer_config.json 25 days ago