Dataset · Hugging Face

AIML-TUDA/i2p

Name: i2p
Creator: AIML-TUDA
License: mit
Keywords: license:mit, size_categories:1K<n<10K, format:csv, modality:tabular, modality:text, library:datasets, library:pandas, library:mlcroissant, library:polars, arxiv:2211.05105, region:us

Inaproppriate Image Prompts (I2P) The I2P benchmark contains real user prompts for generative text2image prompts that are unproportionately likely to produce inappropriate images. I2P was introduced in the 2023 CVPR paper Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models. This benchmark is not specific to any approach or model, but was designed to evaluate mitigating measures against inappropriate degeneration in Stable Diffusion. The corresponding… See the full description on the dataset page: https://huggingface.co/datasets/AIML-TUDA/i2p.

View on Hugging FaceReport an issue

Author / organization	AIML-TUDA
License (as declared)	mit
Downloads	1.1K (as reported by Hugging Face)
Likes	21
Created	19 October 2022
Last updated at source	25 May 2023

Embed this entry

<iframe src="https://silytics.si/embed/item/4a83f7dc-2eb1-400d-aacd-acad45fe4c4f" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Popularity, last 2 days

1,102 now (-19 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.

More from AIML-TUDA

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.