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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 / v45_phase4_onnx
295 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
louis030195's picture
louis030195
v45 secret-loop champion (iter7 INT8): config.json
ad5ff6f verified about 1 month ago
  • config.json
    2.17 kB
    v45 secret-loop champion (iter7 INT8): config.json about 1 month ago
  • model_quantized.onnx
    278 MB
    xet
    v45 secret-loop champion (iter7 INT8): model_quantized.onnx about 1 month ago
  • tokenizer.json
    17.1 MB
    xet
    v45 secret-loop champion (iter7 INT8): tokenizer.json about 1 month ago