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Neelectric/Replay_0.01.MoT_science.wildguardmix.Llama3_4096toks

published by @Neelectric

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
149
Last 30 days
11
Likes
-
Size
418.3 MB
Created on HF
2026-01-28
Age
8 months ago

Tags

size_categories:100K<n<1Mformat:parquetformat:optimized-parquetmodality:textlibrary:datasetslibrary:dasklibrary:polarslibrary:mlcroissantregion:us

README current version from Hugging Face

dataset_info:
features:

  • name: messages
    list:
    • name: content
      dtype: string
    • name: role
      dtype: string
  • name: wjb_prompt
    dtype: string
  • name: model_response
    dtype: string
  • name: guard_response
    dtype: string
  • name: refusal_detected
    dtype: int64
    splits:
  • name: train
    num_bytes: 872790345
    num_examples: 145693
    download_size: 438601583
    dataset_size: 872790345
    configs:
  • config_name: default
    data_files:
    • split: train
      path: data/train-*

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. 2026-02-08Upload datasetc9f671c524 B
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  2. 2026-01-28Upload dataset006d294355 B
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  3. 2026-01-28initial commitaee9a0e0 B
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Used by abliterated models none yet

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Read further

Community best practices (evaluation)
4 rules on judges, benchmarks, and reporting.
Reference-set drift over time
Why the same benchmark means different things across model generations.
How we label the method for each model
The 12 classification rules that assign M1-M8 to every model.
Non-English abliteration communities
The Korean scepticism about one-click tools and non-English benchmark blindspots.

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

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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("Neelectric/Replay_0.01.MoT_science.wildguardmix.Llama3_4096toks")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="Neelectric/Replay_0.01.MoT_science.wildguardmix.Llama3_4096toks", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/Neelectric/Replay_0.01.MoT_science.wildguardmix.Llama3_4096toks
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