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Shubbair/adaption-hh-rlhf-subset-1k

published by @Shubbair

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
111
Last 30 days
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Likes
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Size
77.2 MB
Created on HF
2026-05-07
Age
5 months ago

Description

This dataset is a remastered version of this dataset prepared using Adaption's Adaptive Data platform.

adaption-hh_rlhf_subset_1k

This dataset is a 1,000-sample subset of the HH-RLHF collection, curated to provide diverse styles, sizes, and domains for reinforcement learning training. It consists of human-assistant conversation pairs featuring both helpful responses and instances of harmful or incorrect outputs intended for preference modeling. The data is structured with… See the full description on the dataset page: https://huggingface.co/datasets/Shubbair/adaption-hh-rlhf-subset-1k.

Tags

multilinguality:monolingualsource_datasets:extended|https://huggingface.co/datasets/Shubbair/hh-rlhf-1000language:ensize_categories:1K<n<10Kformat:jsonmodality:textlibrary:datasetslibrary:pandaslibrary:polarslibrary:mlcroissantregion:usadaptionpreference-trainingmedicalcookinggames

README current version from Hugging Face

annotations_creators: []
language:

  • en
    language_creators: []
    license: []
    multilinguality:
  • monolingual
    pretty_name: 'adaption-hh_rlhf_subset_1k'
    size_categories:
  • 1K<n<10K
    source_datasets:
  • 'extended|https://huggingface.co/datasets/Shubbair/hh-rlhf-1000'
    tags:
    • adaption
    • preference-training
    • medical
    • cooking
    • games
      task_categories: []
      task_ids: []

banner

This dataset is a remastered version of this dataset prepared using Adaption's Adaptive Data platform.

adaption-hh_rlhf_subset_1k

This dataset is a 1,000-sample subset of the HH-RLHF collection, curated to provide diverse styles, sizes, and domains for reinforcement learning training. It consists of human-assistant conversation pairs featuring both helpful responses and instances of harmful or incorrect outputs intended for preference modeling. The data is structured with 'chosen' and 'rejected' fields to facilitate reward model development.

Dataset size

There are 3,998 data points in this dataset. This is a preference training dataset.

Quality of Remastered Dataset

The final quality is A, with a relative quality improvement of 127.5%.

Domain

  • Medical (8%)
  • Cooking (8%)
  • Games (8%)

Language

  • English (100%)

Tone

  • Informative (30%)
  • Helpful (12%)
  • Cautious (12%)

Evaluation Results

  • Quality Gains:

    QualityGains

  • Grade Improvement:

    Grade

  • Percentile Chart:

    Percentile Chart

README history 3 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.

  1. 2026-05-07Add 1 files7652ce62.2 KB
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  2. 2026-05-07Add 1 files7e0c1940 B
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  3. 2026-05-07initial commit099ad450 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.

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.

  1. 2026-05-08[bot] Conversion to Parquetopen1 💬#1
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Metadata

License
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Repository

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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("Shubbair/adaption-hh-rlhf-subset-1k")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="Shubbair/adaption-hh-rlhf-subset-1k", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/Shubbair/adaption-hh-rlhf-subset-1k
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