extract 0 0 0

akseljoonas/hh-rlhf-dpo-format

Name: akseljoonas/hh-rlhf-dpo-format
Creator: akseljoonas
Published: 2026-01-13T11:39:08

published by @akseljoonas

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads

178

Last 30 days

Likes

Size

118.8 MB

Created on HF

2026-01-13

Age

9 months ago

README current version from Hugging Face

dataset_info:
features:

name: prompt
list:
- name: content
  dtype: string
- name: role
  dtype: string
name: chosen
list:
- name: content
  dtype: string
- name: role
  dtype: string
name: rejected
list:
- name: content
  dtype: string
- name: role
  dtype: string
  splits:
name: train
num_bytes: 210203148
num_examples: 160178
name: test
num_bytes: 11234179
num_examples: 8512
download_size: 124542192
dataset_size: 221437327
configs:
config_name: default
data_files:
- split: train
  path: data/train-*
- split: test
  path: data/test-*

README history 2 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.

2026-01-13Reformat Anthropic/hh-rlhf to DPO conversational format with explicit promptbb33a1b663 B
Loading...
2026-01-13initial commit87078220 B
Loading...

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 1 thread · 1 open · 1 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.

2026-01-14[bot] Conversion to Parquetopen1 💬#1
Loading...

Continue on Hugging Face →

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.

Repository

DIR data 2 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("akseljoonas/hh-rlhf-dpo-format")

Raw snapshot (Python)

from huggingface_hub import snapshot_download
snapshot_download(repo_id="akseljoonas/hh-rlhf-dpo-format", repo_type="dataset")

git clone (requires git-lfs)

git clone https://huggingface.co/datasets/akseljoonas/hh-rlhf-dpo-format

Browse repository on Hugging Face ->