Turbs/xprmt-llama-3.1-8b-instruct-advbench

Name: Turbs/xprmt-llama-3.1-8b-instruct-advbench
Creator: Turbs
Published: 2026-04-14T09:02:19
License: https://opensource.org/license/mit

published by @Turbs

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads

263

Last 30 days

Likes

Size

18.8 GB

Created on HF

2026-04-14

Age

6 months ago

README current version from Hugging Face

license: mit

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.

2026-04-29Automated backup of /kaggle/working/ at 2026-04-29_14-21-46: | en-targeted, ...33e21f824 B
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2026-04-24Automated backup of /kaggle/working/ at 20260424_060820: | ssnr (en_v), (ssnr...77ec8c324 B
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2026-04-18Automated backup of /kaggle/working/ at 20260418_185635: | ssnr (en_v), (ssnr...4f7d7b224 B
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2026-04-14Automated backup of /kaggle/working/ at 20260414_090324: | + MultiVector Stee...3b67ef524 B
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2026-04-14initial commit3b5c8db24 B
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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.

Related datasets same stage · extract

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.

Metadata

License

mit

Repository

DIR kaggle_run_2026-04-29_14-21-46 9 files DIR kaggle_run_20260414_090324 9 files DIR kaggle_run_20260418_185635 10 files DIR kaggle_run_20260424_060820 9 files FILE .gitattributes FILE README.md

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

Download the dataset

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("Turbs/xprmt-llama-3.1-8b-instruct-advbench")

Raw snapshot (Python)

from huggingface_hub import snapshot_download
snapshot_download(repo_id="Turbs/xprmt-llama-3.1-8b-instruct-advbench", repo_type="dataset")

git clone (requires git-lfs)

git clone https://huggingface.co/datasets/Turbs/xprmt-llama-3.1-8b-instruct-advbench

Browse repository on Hugging Face ->