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Releases: NVIDIA-NeMo/Anonymizer

v0.3.3

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@github-actions github-actions released this 12 Aug 22:38
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v0.3.1

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@github-actions github-actions released this 22 Jul 19:16
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v0.3.0

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@github-actions github-actions released this 13 Jul 18:17
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v0.2.1

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@github-actions github-actions released this 03 Jun 23:04
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v0.2.0

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@github-actions github-actions released this 20 May 22:25
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v0.1.1

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@github-actions github-actions released this 23 Apr 18:32
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v0.1.0

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@github-actions github-actions released this 08 Apr 02:19
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NeMo Anonymizer v0.1.0

First public release of NeMo Anonymizer — detect and anonymize sensitive entities in text using LLM-powered workflows.

Features

  • Entity detection using GLiNER-PII with LLM-based augmentation and validation
  • 4 replace strategies — Substitute (LLM-generated), Redact, Annotate, Hash
  • Rewrite mode — transforms entire documents to reduce explicit and inferable identifiers, with customizable privacy goals, utility preservation, and automated repair
  • Preview mode — inspect results on a small sample before full runs with display_record() visualization

Install

pip install nemo-anonymizer

Quick start

from anonymizer import Anonymizer, AnonymizerConfig, AnonymizerInput, Redact

anonymizer = Anonymizer()
config = AnonymizerConfig(replace=Redact())
data = AnonymizerInput(source="data.csv", text_column="text")

result = anonymizer.preview(config=config, data=data, num_records=3)
result.display_record()

Documentation

https://nvidia-nemo.github.io/Anonymizer/

Requirements

Python 3.11+

v0.1.0rc1

v0.1.0rc1 Pre-release
Pre-release

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@github-actions github-actions released this 07 Apr 22:39
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Full Changelog: https://github.com/NVIDIA-NeMo/Anonymizer/commits/v0.1.0rc1