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 stack for IT teams focusing on data compliance and protecting sensitive information in documents.
How the workflow runs
01anonymizer-ner — Automatically identify and anonymize sensitive data in documents.
02agent-native-cloud — Orchestrate multiple automated workflows for compliance checks and data processing.
03vulnhunter — Scan and assess the security of applications to ensure compliance with data protection regulations.
This combination enhances data security through automation, helping enterprises manage compliance efficiently while minimizing the risk of data breaches.