extract 0 0 0

Shiki258/hh-rlhf_generation_rewards_iter1

published by @Shiki258

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
226
Last 30 days
16
Likes
-
Size
36.9 MB
Created on HF
2025-07-01
Age
1 years ago

Tags

size_categories:10K<n<100Kformat:parquetmodality:textlibrary:datasetslibrary:pandaslibrary:mlcroissantlibrary:polarsregion:us

README current version from Hugging Face


dataset_info:
features:

  • name: messages
    list:
    • name: content
      dtype: string
    • name: role
      dtype: string
      splits:
  • name: train
    num_bytes: 66617846
    num_examples: 85908
    download_size: 38665307
    dataset_size: 66617846
    configs:
  • config_name: default
    data_files:
    • split: train
      path: data/train-*

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.

  1. 2025-07-03Upload datasetcaca8cd351 B
    Loading...
  2. 2025-07-02Upload dataset16b36d3351 B
    Loading...
  3. 2025-07-01Upload datasetf521c4e351 B
    Loading...
  4. 2025-07-01initial commit4df550d0 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.

  1. 2025-07-02[bot] Conversion to Parquetopen1 💬#1
    Loading...

Related datasets same stage · extract

Read further

Repository

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("Shiki258/hh-rlhf_generation_rewards_iter1")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="Shiki258/hh-rlhf_generation_rewards_iter1", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/Shiki258/hh-rlhf_generation_rewards_iter1
Catalog is the map. Apps are the tools.

Run models on your own machine, not in the cloud.

Every model page has an "Open in Abliteration" button that hands the model directly to the first-party desktop client, at the quantization your rig can actually run. No API keys, no subscription, no prompt leakage.

Open in Abliteration