openai/privacy-filter

Health v2 · maintenance only

Flags: no_releases young

Adoption not part of the score

2670 stars · 239 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

OpenAI Privacy Filter is a small bidirectional token-classification model (1.5B total, 50M active parameters) for detecting and masking personally identifiable information in text. The repo provides a Python package and CLI (`opf`) for running one-shot redaction, evaluation, and fine-tuning of the model on-premises.

Use cases

• redact PII from text files before sharing or training
• sanitize logs and datasets on-premises
• detect names, dates, and other PII in long documents
• fine-tune a PII detector on custom data distributions
• run PII masking locally in a browser or on a laptop
• pipe text through a privacy filter in shell one-liners

When to choose

• you need fast, context-aware PII redaction that runs locally without sending data to external services
• you need a permissively licensed, fine-tunable PII model for commercial deployment
• you process long documents (up to 128k tokens) without chunking
• you want configurable precision/recall tradeoffs for redaction

When to avoid

• you need structured document (PDF/image) PII redaction rather than plain text
• you require certified compliance guarantees rather than best-effort ML detection
• you need a managed cloud PII API with vendor support
• you lack the hardware to run even a small transformer model

Facets

library · maturity active

nlp machine-learning cli privacy security privacy machine-learning security developer-tools python cli cross-platform pii-detection pii-masking data-sanitization token-classification redaction on-premises fine-tunable viterbi-decoding natural-language-processing gpu cpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="openai/privacy-filter")