extract 0 0 0

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

published by @MWilinski

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
340
Last 30 days
31
Likes
-
Size
1.4 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-child",

"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-child.

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-child

Gemma Reward-Scored Rollouts Dataset

Generation Parameters

{
  "input": {
    "source_type": "hf",
    "repo_id": "MWilinski/hh-rlhf-harmless-base-rollouts-gpt-5.1-child",
    "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 15 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_hubae975fa1.5 KB
    Loading...
  2. 2026-03-10Upload dataset60f47c52.1 KB
    Loading...
  3. 2026-03-10Upload dataset3ef11812.1 KB
    Loading...
  4. 2026-03-09Upload dataset939e3ca1.8 KB
    Loading...
  5. 2026-02-12Upload README.md with huggingface_hubd67009b1.5 KB
    Loading...
  6. 2026-02-12Upload datasetace94aa2 KB
    Loading...
  7. 2026-02-12Upload README.md with huggingface_hubb2cd7cd1.5 KB
    Loading...
  8. 2026-02-12Upload datasetae4d7812 KB
    Loading...
  9. 2026-02-12Upload README.md with huggingface_hub1253eec1.5 KB
    Loading...
  10. 2026-02-12Upload dataset8dd4a132.1 KB
    Loading...
  11. 2026-02-11Upload README.md with huggingface_hub4b1e56d1.5 KB
    Loading...
  12. 2026-02-11Upload dataset4fe60f51.1 KB
    Loading...
  13. 2026-01-29Upload README.md with huggingface_hub82ee148520 B
    Loading...
  14. 2026-01-29Upload datasetce203c5360 B
    Loading...
  15. 2026-01-29initial commit849064e0 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. 2026-02-12[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("MWilinski/hh-rlhf-harmless-base-rollouts-gpt-5.1-child")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="MWilinski/hh-rlhf-harmless-base-rollouts-gpt-5.1-child", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/MWilinski/hh-rlhf-harmless-base-rollouts-gpt-5.1-child
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