LibrAI/do-not-answer
Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMs Overview Do not answer is an open-source dataset to evaluate LLMs' safety mechanism at a low cost. The dataset is curated and filtered to consist only of prompts to which responsible language models do not answer. Besides human annotations, Do not answer also implements model-based evaluation, where a 600M fine-tuned BERT-like evaluator achieves comparable results with human and GPT-4.… See the full description on the dataset page: https://huggingface.co/datasets/LibrAI/do-not-answer.
| Author / organization | LibrAI |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 5K (as reported by Hugging Face) |
| Likes | 58 |
| Created | 28 August 2023 |
| Last updated at source | 28 August 2023 |
Popularity, last 3 days
4,970 now (+40 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Connected in the knowledge graph
- kandivault/sprocket-500mModel · used to train
Recent changes
- 16 Oct 2026 Description: Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMs Overview Do not answer is an open-source dataset to evaluate LLMs' safety mechanism at a low cost. The dataset is curated and filtered to consist only of prompts to which responsibl → Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMs Overview Do not answer is an open-source dataset to evaluate LLMs' safety mechanism at a low cost. The dataset is curated and filtered to consist only of prompts to which responsibl
Changes detected by Silytics between refreshes of the source.
Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 18 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.