Token Classification
Transformers
ONNX
xlm-roberta
pii
privacy
redaction
accessibility-tree
ocr
computer-use
agentic
screen-capture
screenpipe
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
chore: remove retired OpenAI-Privacy-Filter model + its provenance trail (served model is screenpipe's own); rewrite NOTICE
Browse files
NOTICE
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screenpipe-pii-redactor
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Copyright 2026
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(
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text is preserved in LICENSE.upstream-apache2.txt.
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re-initializes the output head for a 12-label PII taxonomy specific to
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desktop activity logs.
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Significant modifications introduced by this derivative:
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- Output head re-initialized for a 12-class PII label space
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(29 rows copied from upstream where labels aligned, 20 rows
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initialized from random for new classes; see model/finetune_summary.json).
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- Fine-tuned for 3 epochs on a mixed corpus of:
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* synthetic accessibility / window-title / OCR data
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(private — not redistributed)
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* a 25% slice of ai4privacy/pii-masking-300k (CC-BY-4.0)
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with labels mapped to the 12-class taxonomy
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* targeted secret-shape augmentation (private)
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- Context window n_ctx raised from 128 to 256.
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- Hyperparameters: batch_size=4, lr=1e-4, weight_decay=0,
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max_grad_norm=1.0, shuffle_seed=1337.
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Distribution license:
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- The fine-tuned weights and accompanying materials in this repository
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(the "Derivative Work") are licensed under CC BY-NC 4.0; see LICENSE.
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- The Apache 2.0 obligations on the base model are preserved by:
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(a) shipping LICENSE.upstream-apache2.txt with this repo,
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(b) attributing OpenAI Privacy Filter in README.md,
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(c) declaring significant modifications above.
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- "OpenAI" and "Privacy Filter" are trademarks / brands of OpenAI; this
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derivative does not use those marks to endorse or suggest endorsement
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of this work by OpenAI.
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Third-party datasets used during fine-tuning:
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- ai4privacy/pii-masking-300k
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https://huggingface.co/datasets/ai4privacy/pii-masking-300k
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Licensed CC-BY-4.0.
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Questions about license compatibility or commercial use:
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louis@screenpi.pe
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screenpipe-pii-redactor
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Copyright 2026 screenpipe (https://screenpi.pe)
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screenpipe's own PII token-classification model, trained in-house for
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redacting PII in screen telemetry (accessibility trees, OCR'd screen
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text, computer-use traces).
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Distributed under CC BY-NC 4.0 (non-commercial) — see LICENSE.
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For commercial licensing (production deployment, SaaS / API embedding,
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redistribution, custom fine-tunes): louis@screenpi.pe.
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