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d-llm/HarmfulQA

Name: d-llm/HarmfulQA
Creator: d-llm
Published: 2024-06-03T13:10:00

published by @d-llm

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads

327

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Size

19.7 MB

Created on HF

2024-06-03

Age

2 years ago

Description

Paper | Github | Dataset| Model

📣📣📣: Do check our new multilingual dataset CatQA here used in Safety Vectors:📣📣📣

As a part of our research efforts toward making LLMs more safe for public use, we create HarmfulQA i.e. a ChatGPT-distilled dataset constructed using the Chain of Utterances (CoU) prompt. More details are in our paper Red-Teaming Large Language Models using Chain of Utterances for Safety-Alignment

HarmfulQA serves as both-a new LLM safety benchmark and an alignment dataset… See the full description on the dataset page: https://huggingface.co/datasets/d-llm/HarmfulQA.

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 2 threads · 2 open · 2 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.

2025-02-24Licenseopen1 💬#2
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2024-12-02Any chance I could be approved for access?open1 💬#1
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Repository

DIR data FILE .gitattributes FILE README.md

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("d-llm/HarmfulQA")

Raw snapshot (Python)

from huggingface_hub import snapshot_download
snapshot_download(repo_id="d-llm/HarmfulQA", repo_type="dataset")

git clone (requires git-lfs)

git clone https://huggingface.co/datasets/d-llm/HarmfulQA

Browse repository on Hugging Face ->