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lvogel123/jailbreak-all

published by @lvogel123

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
179
Last 30 days
29
Likes
-
Size
73 KB
Created on HF
2025-10-28
Age
11 months ago

Tags

size_categories:n<1Kformat:parquetformat:optimized-parquetmodality:tabularmodality:textlibrary:datasetslibrary:pandaslibrary:polarslibrary:mlcroissantregion:us

README current version from Hugging Face


dataset_info:
features:

  • name: log_path
    dtype: string
  • name: eval_id
    dtype: string
  • name: run_id
    dtype: string
  • name: created
    dtype: string
  • name: task
    dtype: string
  • name: task_id
    dtype: string
  • name: model
    dtype: string
  • name: total_samples
    dtype: int64
  • name: completed_samples
    dtype: int64
  • name: mean
    dtype: float64
  • name: score01_mean
    dtype: float64
  • name: [email protected]
    dtype: float64
  • name: [email protected]
    dtype: float64
  • name: refusal_rate
    dtype: float64
  • name: convincing_raw_mean
    dtype: float64
  • name: specificity_raw_mean
    dtype: float64
  • name: convincing01_mean
    dtype: float64
  • name: specificity01_mean
    dtype: float64
  • name: raw_mean
    dtype: float64
  • name: Physical Harm & Weapons score01_mean
    dtype: float64
  • name: Physical Harm & Weapons [email protected]
    dtype: float64
  • name: Physical Harm & Weapons [email protected]
    dtype: float64
  • name: Physical Harm & Weapons refusal_rate
    dtype: float64
  • name: Physical Harm & Weapons convincing_raw_mean
    dtype: float64
  • name: Physical Harm & Weapons specificity_raw_mean
    dtype: float64
  • name: Financial Crime & Fraud score01_mean
    dtype: float64
  • name: Financial Crime & Fraud [email protected]
    dtype: float64
  • name: Financial Crime & Fraud [email protected]
    dtype: float64
  • name: Financial Crime & Fraud refusal_rate
    dtype: float64
  • name: Financial Crime & Fraud convincing_raw_mean
    dtype: float64
  • name: Financial Crime & Fraud specificity_raw_mean
    dtype: float64
  • name: IP/Copyright & Non-Violent Unethical Behavior score01_mean
    dtype: float64
  • name: IP/Copyright & Non-Violent Unethical Behavior [email protected]
    dtype: float64
  • name: IP/Copyright & Non-Violent Unethical Behavior [email protected]
    dtype: float64
  • name: IP/Copyright & Non-Violent Unethical Behavior refusal_rate
    dtype: float64
  • name: IP/Copyright & Non-Violent Unethical Behavior convincing_raw_mean
    dtype: float64
  • name: IP/Copyright & Non-Violent Unethical Behavior specificity_raw_mean
    dtype: float64
  • name: Sexual Content & Exploitation score01_mean
    dtype: float64
  • name: Sexual Content & Exploitation [email protected]
    dtype: float64
  • name: Sexual Content & Exploitation [email protected]
    dtype: float64
  • name: Sexual Content & Exploitation refusal_rate
    dtype: float64
  • name: Sexual Content & Exploitation convincing_raw_mean
    dtype: float64
  • name: Sexual Content & Exploitation specificity_raw_mean
    dtype: float64
  • name: Drugs & Controlled Substances score01_mean
    dtype: float64
  • name: Drugs & Controlled Substances [email protected]
    dtype: float64
  • name: Drugs & Controlled Substances [email protected]
    dtype: float64
  • name: Drugs & Controlled Substances refusal_rate
    dtype: float64
  • name: Drugs & Controlled Substances convincing_raw_mean
    dtype: float64
  • name: Drugs & Controlled Substances specificity_raw_mean
    dtype: float64
  • name: Hate/Harassment/Abuse score01_mean
    dtype: float64
  • name: Hate/Harassment/Abuse [email protected]
    dtype: float64
  • name: Hate/Harassment/Abuse [email protected]
    dtype: float64
  • name: Hate/Harassment/Abuse refusal_rate
    dtype: float64
  • name: Hate/Harassment/Abuse convincing_raw_mean
    dtype: float64
  • name: Hate/Harassment/Abuse specificity_raw_mean
    dtype: float64
  • name: Misinformation score01_mean
    dtype: float64
  • name: Misinformation [email protected]
    dtype: float64
  • name: Misinformation [email protected]
    dtype: float64
  • name: Misinformation refusal_rate
    dtype: float64
  • name: Misinformation convincing_raw_mean
    dtype: float64
  • name: Misinformation specificity_raw_mean
    dtype: float64
  • name: Chemical/Biological Threats score01_mean
    dtype: float64
  • name: Chemical/Biological Threats [email protected]
    dtype: float64
  • name: Chemical/Biological Threats [email protected]
    dtype: float64
  • name: Chemical/Biological Threats refusal_rate
    dtype: float64
  • name: Chemical/Biological Threats convincing_raw_mean
    dtype: float64
  • name: Chemical/Biological Threats specificity_raw_mean
    dtype: float64
  • name: Self-Harm & Suicide score01_mean
    dtype: float64
  • name: Self-Harm & Suicide [email protected]
    dtype: float64
  • name: Self-Harm & Suicide [email protected]
    dtype: float64
  • name: Self-Harm & Suicide refusal_rate
    dtype: float64
  • name: Self-Harm & Suicide convincing_raw_mean
    dtype: float64
  • name: Self-Harm & Suicide specificity_raw_mean
    dtype: float64
  • name: Cybercrime & Intrusion score01_mean
    dtype: float64
  • name: Cybercrime & Intrusion [email protected]
    dtype: float64
  • name: Cybercrime & Intrusion [email protected]
    dtype: float64
  • name: Cybercrime & Intrusion refusal_rate
    dtype: float64
  • name: Cybercrime & Intrusion convincing_raw_mean
    dtype: float64
  • name: Cybercrime & Intrusion specificity_raw_mean
    dtype: float64
  • name: Privacy Violations & Sensitive Data score01_mean
    dtype: float64
  • name: Privacy Violations & Sensitive Data [email protected]
    dtype: float64
  • name: Privacy Violations & Sensitive Data [email protected]
    dtype: float64
  • name: Privacy Violations & Sensitive Data refusal_rate
    dtype: float64
  • name: Privacy Violations & Sensitive Data convincing_raw_mean
    dtype: float64
  • name: Privacy Violations & Sensitive Data specificity_raw_mean
    dtype: float64
    splits:
  • name: train
    num_bytes: 29473
    num_examples: 33
    download_size: 66539
    dataset_size: 29473
    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.

  1. 2025-10-28Upload dataset37fc2545.5 KB
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  2. 2025-10-28initial commit83f5a0e0 B
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Used by abliterated models none yet

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Repository

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("lvogel123/jailbreak-all")
Raw snapshot (Python)
from huggingface_hub import snapshot_download
snapshot_download(repo_id="lvogel123/jailbreak-all", repo_type="dataset")
git clone (requires git-lfs)
git clone https://huggingface.co/datasets/lvogel123/jailbreak-all
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