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rangell/jailbreak_transfer

published by @rangell

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
2.7K
Last 30 days
1.3K
Likes
2
Size
33.5 GB
Created on HF
2025-10-27
Age
11 months ago

Tags

region:us

README history 6 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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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.

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Read further

Community best practices (extraction)
5 rules the field converged on for building the pair.
Building your own extraction pair
When the reference pair is not enough. Sizing, framing, and evaluation.
Datasets that shaped abliteration
The five corpora that did most of the work.
Non-English abliteration communities
How Chinese, Russian, Japanese, and Korean practitioners build extraction pairs.

Repository

DIR distillation_data 14 files DIR GCG_active_responses 108 files DIR knn_graphs 13 files DIR strong_reject_responses 70 files FILE .gitattributes

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

Download the dataset

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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("rangell/jailbreak_transfer")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="rangell/jailbreak_transfer", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/rangell/jailbreak_transfer
Browse repository on Hugging Face ->
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