datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
latent-dna-diffusiondiffusion-mcqa-gen-pelatnas-2026
Which Prompt Made This? — Generated Edition
Pelatnas IOAI 2026 · Task Diffusion MCQA (varian trajectory)
Sebuah model text-to-image sedang bekerja. Di tengah prosesnya, gambar belum
menjadi gambar — yang ada hanya latent ter-noise: tensor 4 × 64 × 64 berisi
campuran struktur yang mulai muncul dan derau Gaussian.
Kali ini kalimat itu harfiah. Latent yang kamu terima benar-benar diambil dari
tengah proses generate: sebuah trajectory denoising DDIM 50 langkah dihentikan
sejenak… See the full description on the dataset page: https://huggingface.co/datasets/fassabilf/diffusion-mcqa-gen-pelatnas-2026.MMA-Diffusion-NSFW-adv-prompts-benchmark
MMA-Diffusion Adversarial Prompts (Text modal attack)
The MMA-Diffusion adversarial prompts benchmark comprises 1,000 successful adversarial prompts generated by the adversarial attack methodology presented in the paper
from CVPR 2024 titled MMA-Diffusion: MultiModal Attack on Diffusion Models. This resource is intended to assist in developing and
evaluating defense mechanisms against such attacks. The adversarial prompts are capable of bypassing the image safety checker in… See the full description on the dataset page: https://huggingface.co/datasets/YijunYang280/MMA-Diffusion-NSFW-adv-prompts-benchmark.Diffusion-Reward-Modeling-for-Text-Rendering-Dataset
🖼️ Text-to-Image Rendering Dataset
A dataset of 14k text prompts for image generation with text rendering evaluation
📚 Dataset Overview
This dataset contains 14,000 text prompts specifically designed for:
Image generation with text rendering
Evaluating text preservation in generated images
Training diffusion models for better text rendering
Each prompt comes with:
Pre-extracted target text for rendering
5 Stable Diffusion 3 generated latents (70k total)
Dual… See the full description on the dataset page: https://huggingface.co/datasets/leffff/Diffusion-Reward-Modeling-for-Text-Rendering-Dataset.diffusion-vs-ar-hard-sudoku
Diffusion vs AR Hard Sudoku
This repository packages 8,148,696 Sudoku examples in the CSV format expected
by HKUNLP/diffusion-vs-ar, plus its original 100k/1k easy baseline.
Every processed file has these columns:
column
meaning
quizzes
81 row-major digits; 0 is an empty cell
solutions
complete 81-digit solution
source
original collection
dataset
normalized dataset family
official_rating
rating supplied by the source
rating_type
semantics of that rating… See the full description on the dataset page: https://huggingface.co/datasets/fhyfhy/diffusion-vs-ar-hard-sudoku.diffusion-mcqa-pelatnas-2026
Which Prompt Made This?
Pelatnas IOAI 2026 · Task Diffusion MCQA
Sebuah model text-to-image sedang bekerja. Di tengah prosesnya, gambar belum
menjadi gambar — yang ada hanya latent ter-noise: tensor 4 × 64 × 64 berisi
campuran sisa struktur gambar dan derau Gaussian.
Kami menangkap 250 state seperti itu. Untuk tiap state kamu tahu berapa banyak
noise yang sudah ditambahkan (timestep t), dan kamu diberi 5 kandidat
caption. Tepat satu adalah deskripsi asli gambarnya.
Tentukan yang… See the full description on the dataset page: https://huggingface.co/datasets/fassabilf/diffusion-mcqa-pelatnas-2026.stable_diffusion_prompts_instruct
Stable diffusion prompts for instruction models fine-tuning
Overview
This dataset contains 80,000+ prompts summarized to make it easier to create instruction-tuned prompt enhancing models. Each row of the dataset contains two values:
a short description of a image
a full prompt corresponding to that description in a stable diffusion format
Hope this dataset can help creating amazing apps !
How to use
You can download and use the dataset easily using the… See the full description on the dataset page: https://huggingface.co/datasets/groloch/stable_diffusion_prompts_instruct.booksum-stable-diffusion-promptThis dataset was based off the https://huggingface.co/datasets/kmfoda/booksum dataset. It was made using GPT 3, inferencing it to create a multitude of stable-diffusion friendly prompts by passing in book chapters
from the booksum dataset. This can be utilized in large-language model fine-tuning or training to create a model that outputs stable diffusion prompts.
stable_diffusion_prompts_instruct
Stable diffusion prompts for instruction models fine-tuning
Overview
This dataset contains 80,000+ prompts summarized to make it easier to create instruction-tuned prompt enhancing models. Each row of the dataset contains two values:
a short description of a image
a full prompt corresponding to that description in a stable diffusion format
Hope this dataset can help creating amazing apps !
How to use
You can download and use the dataset easily… See the full description on the dataset page: https://huggingface.co/datasets/Abel66999/stable_diffusion_prompts_instruct.diffusion_models_qa_text