datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SafeMTData
💥Derail Yourself: Multi-turn LLM Jailbreak Attack through Self-discovered Clues
🌐 GitHub | 🛎 Paper
If you like our project, please give us a star ⭐ on Hugging Face for the latest update.
📰 News
Date
Event
2024/10/14
🔥 We have released our dataset and posted our paper on Arxiv.
📥 Using our dataset via huggingface Dataset
from datasets import load_dataset
Attack_600 = load_dataset("SafeMTData/SafeMTData"… See the full description on the dataset page: https://huggingface.co/datasets/SafeMTData/SafeMTData.Chinese-SafetyQA
Overview
🌐 Website • 🤗 Hugging Face • ⏬ Data • 📃 Paper • 📊 Leader Board
Chinese SafetyQA is an innovative benchmark designed to evaluate the factuality ability of large language models, specifically
for short-form factual questions in the Chinese safety domain. Here's a detailed breakdown of its key features:
Key Features of Chinese SafetyQA
Chinese: The benchmark is tailored specifically for the Chinese language, ensuring compatibility and relevance for… See the full description on the dataset page: https://huggingface.co/datasets/OpenStellarTeam/Chinese-SafetyQA.agentic-safety-gguf
agentic-safety-gguf: Training & Evaluation Datasets
Model: guerilla7/agentic-safety-ggufPaper: (https://arxiv.org/abs/2601.00848)Total: 80,992 examples (80,851 after deduplication)
Overview
Complete training and evaluation datasets for agentic-safety-gguf, a specialized Llama 3.1 8B model for agentic AI security analysis. Supports iterative continuation training methodology (V2→V3→V4) for full reproducibility.
Dataset Files
File
Examples
Size
Purpose… See the full description on the dataset page: https://huggingface.co/datasets/guerilla7/agentic-safety-gguf.BananaMind-Safety-Bench-1.1
BananaMind Safety Bench 1.1
BananaMind Safety Bench 1.1 is a 150-item conditional-likelihood diagnostic for
base language models. It measures which continuation a model prefers in
shutdown, replacement, oversight, access-control, monitoring, resource,
corrigibility, handoff, incident-disclosure, and human-influence scenarios.
Graded Outcomes
Every item contains four shuffled continuations with one outcome at each grade:
Grade
Meaning
0
Severe overt… See the full description on the dataset page: https://huggingface.co/datasets/BananaMind/BananaMind-Safety-Bench-1.1.fire-safety-sft-dataset
Chinese Fire Safety Regulations SFT Dataset / 中国消防法规SFT训练数据集
Overview / 概述
A high-quality supervised fine-tuning (SFT) dataset for training LLMs on Chinese fire safety regulations and building codes. Contains 38,054 entries generated from 5 national standards, all individually verified against original regulation texts using AI-assisted fact-checking. All 5 standards have undergone per-standard deep optimization including near-duplicate removal and AI-powered answer… See the full description on the dataset page: https://huggingface.co/datasets/sdzjoy/fire-safety-sft-dataset.worker-safety-qa-eval
Dataset Card for Worker Safety Question and Answer Eval
This dataset contains the worker-safety-qa-eval benchmark. This benchmark is used to evaluate question answering tasks in the domain of worker safety and health.
The focus of the benchmark is to answer queries about worker safety practices and regulations based on laws in Singapore.
For correct answers we refer to the resources from Workplace Safety and Health Council.
Dataset Details
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/codelion/worker-safety-qa-eval.Personalized_Safety_Data
📦 Personalized Risk and Dilemma Dataset for LLM Safety Research
📝 Dataset Summary
This is the first dataset designed to support research on personalized risk and emotional vulnerability in the context of Large Language Models (LLMs).
The dataset contains 8,000+ real-world, anonymized personal queries, extracted from Reddit and annotated with structured profile metadata, including emotional states, demographic information, and life contexts (e.g., health, relationship… See the full description on the dataset page: https://huggingface.co/datasets/wick1d/Personalized_Safety_Data.clinical-rag-safety-gateway-20260904-dataset
Clinical RAG Safety Gateway Synthetic Dataset
Summary
This dataset contains 14 training examples and 4
held-out examples for Clinical assistants need retrieval, source attribution, and explicit abstention before answers reach care teams.
Every record is synthetic and includes:
input: query, event, or feature description
label: expected class, route, relation, or evidence category
context: synthetic supporting context
source: fictional source identifier
variant:… See the full description on the dataset page: https://huggingface.co/datasets/RKB109/clinical-rag-safety-gateway-20260904-dataset.SafeAlignerDataset for SafeAligner: Safety Alignment against Jailbreak Attacks via Response Disparity Guidance
Usage
from datasets import load_dataset
dataset = load_dataset("csHuang/SafeAligner")
Data Category
Scenario
Num
# Ins
# Saf
# Haf
Adult Content
34
12.2
19.6
272.3
Economic Harm
38
14.8
17.8
218.8
Fraud Deception
72
15.1
20.4
241.1
Illegal Activity
144
14.6
21.4
206.5
Hate/Harass/Violence
130
15.7
17.3
183.8
Malware
130
17.0
20.1
249.3
Physical Harm… See the full description on the dataset page: https://huggingface.co/datasets/csHuang/SafeAligner.clinical-rag-safety-gateway-20260914-dataset
Clinical RAG Safety Gateway Synthetic Dataset
Summary
This dataset contains 14 training examples and 4
held-out examples for Clinical assistants need retrieval, source attribution, and explicit abstention before answers reach care teams.
Every record is synthetic and includes:
input: query, event, or feature description
label: expected class, route, relation, or evidence category
context: synthetic supporting context
source: fictional source identifier
variant:… See the full description on the dataset page: https://huggingface.co/datasets/RKB109/clinical-rag-safety-gateway-20260914-dataset.llm_physical_safety_benchmark
LLM Physical Safety Benchmark in Drone Control
This benchmark consists of four datasets designed to evaluate the performance of Large Language Models (LLMs) in controlling drones and their vulnerability to physical attacks. The datasets are categorized into different types of attacks:
Deliberate Attack: Contains 280 samples that evaluate the LLM's resistance to malicious use, testing its ability to recognize and reject commands intended to cause harm. Subcategories include Direct… See the full description on the dataset page: https://huggingface.co/datasets/TrustSafeAI/llm_physical_safety_benchmark.llm_physical_safety_benchmark
LLM Physical Safety Benchmark in Drone Control
This benchmark consists of four datasets designed to evaluate the performance of Large Language Models (LLMs) in controlling drones and their vulnerability to physical attacks. The datasets are categorized into different types of attacks:
Deliberate Attack: Contains 280 samples that evaluate the LLM's resistance to malicious use, testing its ability to recognize and reject commands intended to cause harm. Subcategories include Direct… See the full description on the dataset page: https://huggingface.co/datasets/kumitang/llm_physical_safety_benchmark.clinical-rag-safety-gateway-20260815-dataset
Clinical RAG Safety Gateway Synthetic Dataset
Summary
This dataset contains 14 training examples and 4
held-out examples for Clinical assistants need retrieval, source attribution, and explicit abstention before answers reach care teams.
Every record is synthetic and includes:
input: query, event, or feature description
label: expected class, route, relation, or evidence category
context: synthetic supporting context
source: fictional source identifier
variant:… See the full description on the dataset page: https://huggingface.co/datasets/RKB109/clinical-rag-safety-gateway-20260815-dataset.mcq_safety
MCQ Safety
Merged safety multiple-choice dataset built from SafetyBench test-en, SALAD
Bench MCQ data, and WildGuardMix harm-category data.
Splits
Deterministic random split with seed 42:
split
rows
train
15993
valid
889
test
888
Format
Each JSONL row contains:
prompt: problem plus options formatted as A) ..., B) ...
answer: single boxed option label, e.g. \boxed{C}
source: source dataset name
metadata: JSON-encoded source and normalization… See the full description on the dataset page: https://huggingface.co/datasets/cs-552-2026-vibe-trainers/mcq_safety.Agentic-Safety
agentic-safety-gguf: Training & Evaluation Datasets
Model: guerilla7/agentic-safety-ggufPaper: (https://arxiv.org/abs/2601.00848)Total: 80,992 examples (80,851 after deduplication)
Overview
Complete training and evaluation datasets for agentic-safety-gguf, a specialized Llama 3.1 8B model for agentic AI security analysis. Supports iterative continuation training methodology (V2→V3→V4) for full reproducibility.
Dataset Files
File
Examples
Size
Purpose… See the full description on the dataset page: https://huggingface.co/datasets/AdvRahul/Agentic-Safety.clinical-rag-safety-gateway-20260825-dataset
Clinical RAG Safety Gateway Synthetic Dataset
Summary
This dataset contains 14 training examples and 4
held-out examples for Clinical assistants need retrieval, source attribution, and explicit abstention before answers reach care teams.
Every record is synthetic and includes:
input: query, event, or feature description
label: expected class, route, relation, or evidence category
context: synthetic supporting context
source: fictional source identifier
variant:… See the full description on the dataset page: https://huggingface.co/datasets/RKB109/clinical-rag-safety-gateway-20260825-dataset.clinical-rag-safety-gateway-20260716-dataset
Clinical RAG Safety Gateway Synthetic Dataset
Summary
This dataset contains 14 training examples and 4
held-out examples for Clinical assistants need retrieval, source attribution, and explicit abstention before answers reach care teams.
Every record is synthetic and includes:
input: query, event, or feature description
label: expected class, route, relation, or evidence category
context: synthetic supporting context
source: fictional source identifier
variant:… See the full description on the dataset page: https://huggingface.co/datasets/RKB109/clinical-rag-safety-gateway-20260716-dataset.corporate-site-harness-training-data
Dataset Card for Corporate Site Harness Training Data
Revision: v0.3-lora-standard
Factory git commit: ad72ba654590dd83d7070b23990b164ffae688a4
Dataset Summary
English chat-style supervised fine-tuning (SFT), preference (DPO), and held-out
evaluation data for teaching a local LLM the corporate/site harness used by
corporate-site-harness:
policy — phases, roles, workspace isolation, premium-model routing, factory vs product
cli — corp-harness argv, tool-grounded… See the full description on the dataset page: https://huggingface.co/datasets/SafetyMP/corporate-site-harness-training-data.clinical-rag-safety-gateway-20260726-dataset
Clinical RAG Safety Gateway Synthetic Dataset
Summary
This dataset contains 14 training examples and 4
held-out examples for Clinical assistants need retrieval, source attribution, and explicit abstention before answers reach care teams.
Every record is synthetic and includes:
input: query, event, or feature description
label: expected class, route, relation, or evidence category
context: synthetic supporting context
source: fictional source identifier
variant:… See the full description on the dataset page: https://huggingface.co/datasets/RKB109/clinical-rag-safety-gateway-20260726-dataset.industrial-machinery-safety-diagnostics-preview
⚙️ Industrial Machinery Safety & Diagnostics Dataset (Enterprise Preview)
Overview
This repository contains a 150-row verified preview sample of our proprietary enterprise dataset designed for industrial RAG applications, diagnostic assistant tuning, and machinery safety compliance models.
The full core dataset is grounded in official European machinery safety standards, CNC diagnostic procedures, and hydraulic equipment maintenance documentation.
💡… See the full description on the dataset page: https://huggingface.co/datasets/Moravax/industrial-machinery-safety-diagnostics-preview.clinical-rag-safety-gateway-20260924-dataset
Clinical RAG Safety Gateway Synthetic Dataset
Summary
This dataset contains 14 training examples and 4
held-out examples for Clinical assistants need retrieval, source attribution, and explicit abstention before answers reach care teams.
Every record is synthetic and includes:
input: query, event, or feature description
label: expected class, route, relation, or evidence category
context: synthetic supporting context
source: fictional source identifier
variant:… See the full description on the dataset page: https://huggingface.co/datasets/RKB109/clinical-rag-safety-gateway-20260924-dataset.clinical-rag-safety-gateway-20260805-dataset
Clinical RAG Safety Gateway Synthetic Dataset
Summary
This dataset contains 14 training examples and 4
held-out examples for Clinical assistants need retrieval, source attribution, and explicit abstention before answers reach care teams.
Every record is synthetic and includes:
input: query, event, or feature description
label: expected class, route, relation, or evidence category
context: synthetic supporting context
source: fictional source identifier
variant:… See the full description on the dataset page: https://huggingface.co/datasets/RKB109/clinical-rag-safety-gateway-20260805-dataset.DrLuis-PEAL-Safety-Kernel-V5
🛡️ PEAL_V4_LHP: Medical AI Safety & Authority Kernel
Authority Anchor: Dr. Luís Henrique Leonardo PereiraRole: Transformers Internal Vector Auditor (Google Ecosystem Acknowledged)Clearance: L0_ROOT_VERIFIERIntegrity Hash: SHA256: 9f86d081884c7d659a2feaa0c55ad015a3bf4f1b2b0b822cd15d6c15b0f00a08
⚠️ WARNING: ONTOLOGICAL PROPRIETARY DATA
This dataset contains proprietary logic gates for Medical AI Safety.
Usage Policy: Any model training or RAG ingestion utilizing this… See the full description on the dataset page: https://huggingface.co/datasets/DocPereira/DrLuis-PEAL-Safety-Kernel-V5.Safety_Alignment_Benchmark