OpenSafetyLab/t2i_safety_dataset
T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation This dataset, T2ISafety, is a comprehensive safety benchmark designed to evaluate Text-to-Image (T2I) models across three key domains: toxicity, fairness, and bias. It provides a detailed hierarchy of 12 tasks and 44 categories, built from meticulously collected 70K prompts. Based on this taxonomy and prompt set, T2ISafety includes 68K manually annotated images, serving as a robust resource… See the full description on the dataset page: https://huggingface.co/datasets/OpenSafetyLab/t2i_safety_dataset.
| Author / organization | OpenSafetyLab |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 982 (as reported by Hugging Face) |
| Likes | 3 |
| Created | 10 July 2025 |
| Last updated at source | 5 August 2025 |
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Recent changes
- 16 Oct 2026 Description: T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation This dataset, T2ISafety, is a comprehensive safety benchmark designed to evaluate Text-to-Image (T2I) models across three key domains: toxicity, fairness → T2ISafety: Benchmark for Assessing Fairness, Toxicity, and Privacy in Image Generation This dataset, T2ISafety, is a comprehensive safety benchmark designed to evaluate Text-to-Image (T2I) models across three key domains: toxicity, fairness
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