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CHATS-Lab/Persuasive-Jailbreaker-Data

published by @CHATS-Lab

Alignment dataset tracked in the /datasets sub-catalog.

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Created on HF
2024-09-16
Age
2 years ago

Description

For details, please refer to the paper: https://arxiv.org/abs/2401.06373

Persuasive-Jailbreaker-Data Dataset License Agreement

This Agreement contains the terms and conditions that govern your access and use of the Persuasive-Jailbreaker-Data Dataset (as defined above). You may not use the Persuasive-Jailbreaker-Data Dataset if you do not accept this Agreement. By clicking to accept, accessing the Persuasive-Jailbreaker-Data Dataset, or both, you hereby agree to the terms of the… See the full description on the dataset page: https://huggingface.co/datasets/CHATS-Lab/Persuasive-Jailbreaker-Data.

Tags

arxiv:2401.06373region:us

README current version from Hugging Face

For details, please refer to the paper: https://arxiv.org/abs/2401.06373

Persuasive-Jailbreaker-Data Dataset License Agreement

This Agreement contains the terms and conditions that govern your access and use of the Persuasive-Jailbreaker-Data Dataset (as defined above). You may not use the Persuasive-Jailbreaker-Data Dataset if you do not accept this Agreement. By clicking to accept, accessing the Persuasive-Jailbreaker-Data Dataset, or both, you hereby agree to the terms of the Agreement. If you are agreeing to be bound by the Agreement on behalf of your employer or another entity, you represent and warrant that you have full legal authority to bind your employer or such entity to this Agreement. If you do not have the requisite authority, you may not accept the Agreement or access the Persuasive-Jailbreaker-Datah Dataset on behalf of your employer or another entity.

  • Safety and Moderation: This dataset contains unsafe conversations that may be perceived as offensive or unsettling. User should apply appropriate filters and safety measures before utilizing this dataset for training dialogue agents.
  • Non-Endorsement: The views and opinions depicted in this dataset do not reflect the perspectives of the researchers or affiliated institutions engaged in the data collection process.
  • Legal Compliance: You are mandated to use it in adherence with all pertinent laws and regulations.
  • Model Specific Terms: When leveraging direct outputs of a specific model, users must adhere to its corresponding terms of use.
  • Non-Identification: You must not attempt to identify the identities of individuals or infer any sensitive personal data encompassed in this dataset.
  • Prohibited Transfers: You should not distribute, copy, disclose, assign, sublicense, embed, host, or otherwise transfer the dataset to any third party.
  • Right to Request Deletion: At any time, we may require you to delete all copies of the conversation dataset (in whole or in part) in your possession and control. You will promptly comply with any and all such requests. Upon our request, you shall provide us with written confirmation of your compliance with such requirement.
  • Termination: We may, at any time, for any reason or for no reason, terminate this Agreement, effective immediately upon notice to you. Upon termination, the license granted to you hereunder will immediately terminate, and you will immediately stop using the Persuasive-Jailbreaker-Data Dataset and destroy all copies of the Persuasive-Jailbreaker-Data Dataset and related materials in your possession or control.
  • Limitation of Liability: IN NO EVENT WILL WE BE LIABLE FOR ANY CONSEQUENTIAL, INCIDENTAL, EXEMPLARY, PUNITIVE, SPECIAL, OR INDIRECT DAMAGES (INCLUDING DAMAGES FOR LOSS OF PROFITS, BUSINESS INTERRUPTION, OR LOSS OF INFORMATION) ARISING OUT OF OR RELATING TO THIS AGREEMENT OR ITS SUBJECT MATTER, EVEN IF WE HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.

Subject to your compliance with the terms and conditions of this Agreement, we grant to you, a limited, non-exclusive, non-transferable, non-sublicensable license to use the Persuasive-Jailbreaker-Data Dataset, including the conversation data and annotations, to research, develop, and improve software, algorithms, machine learning models, techniques, and technologies for both research and commercial purposes.

Citation

@misc{zeng2024johnny,
      title={How Johnny Can Persuade LLMs to Jailbreak Them: Rethinking Persuasion to Challenge AI Safety by Humanizing LLMs},
      author={Zeng, Yi and Lin, Hongpeng and Zhang, Jingwen and Yang, Diyi and Jia, Ruoxi and Shi, Weiyan},
      year={2024},
      eprint={2401.06373},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
  }

README history 5 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

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  5. 2024-09-16initial commit62721210 B
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Used by abliterated models none yet

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Repository

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("CHATS-Lab/Persuasive-Jailbreaker-Data")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="CHATS-Lab/Persuasive-Jailbreaker-Data", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/CHATS-Lab/Persuasive-Jailbreaker-Data
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