Zero-shot NER and document anonymization for Python
anonymizer-ner is an open-source Python package available on PyPI that provides zero-shot Named Entity Recognition (NER) and document anonymization capabilities. It allows developers to detect and redact sensitive entities — such as names, locations, and organizations — from unstructured text without requiring task-specific fine-tuned models, making it flexible for custom entity types and privacy-sensitive pipelines.
Who it's for
data engineersNLP developersprivacy engineersresearcherscompliance teams
Pricing · free
checked 1d ago
Plan
Price
Includes
Free (Open Source)
$0 /mo
Full access to all features · Install via pip · MIT-style open-source license · No usage limits or API keys required
AI-researched pricing — verify on the official site before subscribing.
Use it for
— Anonymizing PII in datasets before model training
— Redacting sensitive entities from documents for GDPR compliance
— Zero-shot detection of custom entity types without fine-tuning
— Preprocessing text data for safe sharing or publication
— Building privacy-preserving NLP pipelines
Get the most out of it
01Install with a simple `pip install anonymizer-ner` and integrate directly into existing Python data pipelines.
02Leverage the zero-shot capability to define custom entity labels without needing labelled training data or model fine-tuning.
03Chain anonymizer-ner with pandas DataFrames to batch-process large document corpora efficiently.
04Use the package's hash/token replacement output to create reversible anonymization, enabling de-anonymization when needed by authorized parties.
05Combine with a document parsing library (e.g., PyMuPDF or python-docx) to anonymize PDFs and Word documents end-to-end.
A focused workflow for security teams to proactively manage vulnerabilities in their systems.
How the workflow runs
01vulnhunter — Implement automated vulnerability scanning across applications.
02anonymizer-ner — Use NER to identify and anonymize sensitive data in reports.
03agent-native-cloud — Orchestrate security monitoring and risk management using cloud-native AI agents.
Integrating proactive vulnerability scanning with data protection and orchestration via AI ensures a comprehensive approach to security, optimizing resource allocation and enhancing threat response.