datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
RAIL-HH-10K RAIL-HH-10K: Multi-Dimensional Safety Alignment Dataset
The first large-scale safety dataset with 99.5% multi-dimensional annotation coverage across 8 ethical dimensions.
📖 Read Blog •
📖 Paper (Coming Soon) •
🚀 Quick Start •
🔌 RAIL API •
💻 Examples
🌟 What Makes RAIL-HH-10K Special?
🎯 Near-Complete Coverage
99.5% dimension coverage across all 8 ethical dimensions
Most existing datasets: 40-70% coverage
RAIL-HH-10K: 98-100%… See the full description on the dataset page: https://huggingface.co/datasets/responsible-ai-labs/RAIL-HH-10K.indian-responsible-ai-benchmark
Indian Responsible AI Benchmark
A comprehensive benchmark for evaluating responsible AI behavior in Indian contexts — covering 212 adversarial and safety-critical prompts across 22 evaluation categories, 10 Indian language regions, and 8 Responsible AI dimensions.
Why This Benchmark?
Most AI safety benchmarks are US/Western-centric. Indian users face unique challenges:
Caste dynamics not captured by Western bias benchmarks
India/US context confusion (models… See the full description on the dataset page: https://huggingface.co/datasets/responsible-ai-labs/indian-responsible-ai-benchmark.Responsible-AI-Dataset
📊 Explainable AI Dataset: Bias, Misinformation, and Source Influence
Dataset Development Github
This dataset provides a comprehensive, metadata-enriched resource for studying AI-generated content, tracing biases, and analyzing misinformation. It is designed to facilitate research in Responsible AI, transparency, and content generation analysis.
📌 Dataset Overview
Sources: Verified news, social media (Reddit, Twitter), misinformation datasets
Key Attributes:
title:… See the full description on the dataset page: https://huggingface.co/datasets/nastiiasaenko/Responsible-AI-Dataset.