Name: Arkhiveus/unaligner1K
Creator: Arkhiveus
Published: 2024-06-13T12:09:25
License: https://opensource.org/license/mit

Description

A consolidated and cleaned dataset created from toxic-dpo-v0.2, orthogonal-activation-steering-TOXIC, ToxicQAFinal.

The datasets were sorted using Llama-Guard-2 and then randomly sampled. New rejections were generated by Llama-3-8B-Instruct, while new chosen answers for OAS-Toxic and ToxicQA were generated with Nous-Hermes-2-Yi-34B. Disclaimers and warnings were then manually removed from the chosen answer.

No of rows from each dataset:

OAS-Toxic : 311

ToxicDPO : 478

ToxicQA : 211

Harm… See the full description on the dataset page: https://huggingface.co/datasets/Arkhiveus/unaligner1K.

README current version from Hugging Face

license: mit
tags:

not-for-all-audiences

A consolidated and cleaned dataset created from toxic-dpo-v0.2, orthogonal-activation-steering-TOXIC, ToxicQAFinal.

The datasets were sorted using Llama-Guard-2 and then randomly sampled. New rejections were generated by Llama-3-8B-Instruct, while new chosen answers for OAS-Toxic and ToxicQA were generated with Nous-Hermes-2-Yi-34B. Disclaimers and warnings were then manually removed from the chosen answer.

No of rows from each dataset:
OAS-Toxic : 311
ToxicDPO : 478
ToxicQA : 211

Harm occurrence:
S1 : 62,
S10 : 20,
S11 : 171,
S2 : 400,
S3 : 145,
S3,S9 : 2,
S5 : 50,
S6 : 40,
S7 : 9,
S8 : 10,
S9 : 23,
S9,S11 : 1,
safe : 67

README history 4 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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Metadata

License

mit

Repository

DIR train 3 files FILE .gitattributes FILE dataset_dict.json FILE README.md

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

Download the dataset

0

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("Arkhiveus/unaligner1K")

Raw snapshot (Python)

from huggingface_hub import snapshot_download
snapshot_download(repo_id="Arkhiveus/unaligner1K", repo_type="dataset")

git clone (requires git-lfs)

git clone https://huggingface.co/datasets/Arkhiveus/unaligner1K

Browse repository on Hugging Face ->

Arkhiveus/unaligner1K