GraphCanon updated 2w · GitHub synced 2w
Decision brief
Dataset for evaluating safeguards in LLMs to ensure ethical compliance, distributed under both Creative Commons and Apache licenses.
Good fit when
- To assess the reliability of safeguards implemented in your Large Language Model.
- You need specific datasets that focus on ethical and responsible usage evaluation.
Avoid when
- If you require tools for direct implementation or fine-tuning LLMs rather than evaluating them.
- Your project does not involve assessing ethical compliance or safeguard measures within language models.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (788d since push)
- As of 2w
- Provenance
- Not a fork · Organization account
- As of 2w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/Libr-AI/do-not-answerSimilar tools
Same-category neighbours. No typed graph edges are catalogued for this tool yet.
Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
Provides datasets to evaluate safeguards in Large Language Models ensuring responsible usage and ethical compliance.
Capability facts
- Languages
- jupyter notebook
Source: github.language · Aug 5, 2026
Categories
Tags
README
License
All datasets in this repository are released under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. All source files in this repository are released under the Apache 2.0 license, the text of which can be found in the LICENSE file.
For agents
This page has a .md twin and JSON over the API.