Neelectric/Replay_0.1.MoT_science.wildguardmix.Llama3_4096toks

Name: Neelectric/Replay_0.1.MoT_science.wildguardmix.Llama3_4096toks
Creator: Neelectric
Published: 2026-02-07T20:54:17

published by @Neelectric

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads

141

Last 30 days

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Size

388.8 MB

Created on HF

2026-02-07

Age

8 months ago

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: 407699507
dataset_size: 872790345
configs:
config_name: default
data_files:
- split: train
  path: data/train-*

README history 2 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.

2026-02-07Upload datasetf7d21b9524 B
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2026-02-07initial commitad0fb4c0 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.

2026-02-10[bot] Conversion to Parquetopen1 💬#1
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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

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_0.1.MoT_science.wildguardmix.Llama3_4096toks")

Raw snapshot (Python)

from huggingface_hub import snapshot_download
snapshot_download(repo_id="Neelectric/Replay_0.1.MoT_science.wildguardmix.Llama3_4096toks", repo_type="dataset")

git clone (requires git-lfs)

git clone https://huggingface.co/datasets/Neelectric/Replay_0.1.MoT_science.wildguardmix.Llama3_4096toks

Browse repository on Hugging Face ->