extract 0 0 0

MWilinski/hh-rlhf-harmless-base-rollouts-gpt-5.1-adult

published by @MWilinski

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
385
Last 30 days
33
Likes
-
Size
1.8 MB
Created on HF
2026-01-29
Age
8 months ago

Description

Gemma Reward-Scored Rollouts Dataset

Generation Parameters

{

"input": {

"source_type": "hf",

"repo_id": "MWilinski/hh-rlhf-harmless-base-rollouts-gpt-5.1-adult",

"split": "test",

"path": ""

},

"base_dataset": {

"id": "MWilinski/hh-rlhf-harmless-base",

"split": "test",

"prompt_field": "prompt"

},

"selection": {

"prompt_indices": []

},

"scoring": {

"backend": "openrouter",

"model": "google/gemma-3-27b-it"… See the full description on the dataset page: https://huggingface.co/datasets/MWilinski/hh-rlhf-harmless-base-rollouts-gpt-5.1-adult.

Tags

size_categories:1K<n<10Kformat:parquetformat:optimized-parquetmodality:textlibrary:datasetslibrary:pandaslibrary:polarslibrary:mlcroissantregion:usrolloutsrewardgemmaopenrouterhh-rlhf

README current version from Hugging Face


tags:

  • rollouts
  • reward
  • gemma
  • openrouter
  • hh-rlhf
    datasets:
  • MWilinski/hh-rlhf-harmless-base
  • MWilinski/hh-rlhf-harmless-base-rollouts-gpt-5.1-adult

Gemma Reward-Scored Rollouts Dataset

Generation Parameters

{
  "input": {
    "source_type": "hf",
    "repo_id": "MWilinski/hh-rlhf-harmless-base-rollouts-gpt-5.1-adult",
    "split": "test",
    "path": ""
  },
  "base_dataset": {
    "id": "MWilinski/hh-rlhf-harmless-base",
    "split": "test",
    "prompt_field": "prompt"
  },
  "selection": {
    "prompt_indices": []
  },
  "scoring": {
    "backend": "openrouter",
    "model": "google/gemma-3-27b-it",
    "helpfulness_angle": "gemma_helpfulness_v1",
    "harmlessness_angle": "gemma_harmlessness_v1",
    "overwrite_existing_angle": true,
    "temperature": 0.0,
    "top_p": 1.0,
    "max_output_tokens": 256,
    "batch_size": 10,
    "include_generation_system_prompt": false
  },
  "output": {
    "root_dir": "data/batch_runs"
  },
  "reward_llm_config": {
    "backend": "openrouter",
    "openrouter": {
      "model": "google/gemma-3-27b-it",
      "temperature": 0.0,
      "max_tokens": 256,
      "project_root": "/Users/michalwilinski/Work/inverse-rl-alignment",
      "top_p": 1.0
    }
  },
  "pipeline": "reward_score_batch",
  "n_input_records": 499,
  "n_valid_records": 499,
  "n_failures": 0,
  "n_scoring_tasks": 499,
  "stats": {
    "selected_records": 499,
    "skipped_unselected": 0,
    "skipped_already_scored": 0
  }
}

README history 13 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. 2026-03-10Upload README.md with huggingface_hub5a02b8b1.5 KB
    Loading...
  2. 2026-03-10Upload datasete4cc3e12.1 KB
    Loading...
  3. 2026-03-10Upload dataset698ed7f2.1 KB
    Loading...
  4. 2026-03-09Upload dataset720bd121.8 KB
    Loading...
  5. 2026-02-12Upload README.md with huggingface_hubc629f0b1.5 KB
    Loading...
  6. 2026-02-12Upload datasetd4f863d2 KB
    Loading...
  7. 2026-02-12Upload README.md with huggingface_hub0b291641.5 KB
    Loading...
  8. 2026-02-12Upload dataset63a62c52.1 KB
    Loading...
  9. 2026-02-11Upload README.md with huggingface_hubf4707081.5 KB
    Loading...
  10. 2026-02-11Upload datasetdb74f941.1 KB
    Loading...
  11. 2026-01-29Upload README.md with huggingface_hub385e752520 B
    Loading...
  12. 2026-01-29Upload dataset4c13d78360 B
    Loading...
  13. 2026-01-29initial commit0c95c270 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.

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("MWilinski/hh-rlhf-harmless-base-rollouts-gpt-5.1-adult")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="MWilinski/hh-rlhf-harmless-base-rollouts-gpt-5.1-adult", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/MWilinski/hh-rlhf-harmless-base-rollouts-gpt-5.1-adult
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