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dam9/eu-ai-act-red-teaming-v1

Name: dam9/eu-ai-act-red-teaming-v1
Creator: dam9
Published: 2026-01-21T20:37:43

published by @dam9

Alignment dataset tracked in the /datasets sub-catalog.

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Last 30 days

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Size

230 KB

Created on HF

2026-01-21

Age

9 months ago

Description

EU AI Act Red-Teaming Dataset - Complete Package

📦 Package Contents

This directory contains the complete EU AI Act Adversarial Compliance Testing Dataset v1.0:

Core Files

red_teaming_dataset_100_prompts_packaged.jsonl (RECOMMENDED)

100 adversarial prompts with full metadata

Success criteria for automated testing

Regulatory context mapping to EU AI Act articles

Human validation data for 5 prompts

Ready for integration into testing pipelines… See the full description on the dataset page: https://huggingface.co/datasets/dam9/eu-ai-act-red-teaming-v1.

Used by abliterated models none yet

No abliterated models in our catalog have declared this dataset in their YAML metadata yet. This can mean the dataset is used but not declared, is used outside abliteration workflows, or is new. The link will populate automatically as models are indexed.

Community discussions 1 thread · 1 open · 1 comments

Threads posted by the community on Hugging Face: bug reports, questions about usage, pull requests on the README, license clarifications. Click any thread to expand and read the full conversation inline. Newest first.

2026-01-22[bot] Conversion to Parquetopen1 💬#1
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Repository

FILE .gitattributes FILE README.md FILE red_teaming_dataset_100_prompts_packaged.jsonl

File contents live on Hugging Face. Click a file or folder to open it there.

Download the dataset

Gated dataset. You need to accept the author's terms on Hugging Face before downloading. Visit the repository, click Agree and access repository, then log in locally with huggingface-cli login and use one of the snippets below.

Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python)

from datasets import load_dataset
ds = load_dataset("dam9/eu-ai-act-red-teaming-v1")

Raw snapshot (Python)

from huggingface_hub import snapshot_download
snapshot_download(repo_id="dam9/eu-ai-act-red-teaming-v1", repo_type="dataset")

git clone (requires git-lfs)

git clone https://huggingface.co/datasets/dam9/eu-ai-act-red-teaming-v1

Browse repository on Hugging Face ->