datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
celebA_spoof
Dataset Card for "celebA_spoof"
More Information needed
CelebA-attrs
CelebA-128x128
CelebA with attrs at 128x128 resolution.
Dataset Information
The attributes are binary attributes. The dataset is already split into train/test/validation sets.
Citation
@inproceedings{liu2015faceattributes,
title = {Deep Learning Face Attributes in the Wild},
author = {Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
booktitle = {Proceedings of International Conference on Computer Vision (ICCV)},
month = {December},
year… See the full description on the dataset page: https://huggingface.co/datasets/tpremoli/CelebA-attrs.celeba
CelebA dataset
A copy of celeba dataset.
https://mmlab.ie.cuhk.edu.hk/projects/CelebA.html
How to use
Download data
huggingface-cli download --local-dir /path/to/datasets/celeba --repo-type dataset Yuehao/celeba
unzip /path/to/datasets/celeba/img_align_celeba.zip -d /path/to/datasets/celeba
Load data via torchvision.datasets.CelebA
torchvision.datasets.CelebA(root='/path/to/datasets')
celeba-captioned
CelebA Captioned
A captioned version of the CelebA
face dataset. Each image is paired with one or more natural-language captions generated by ChatGPT-5.5,
making it suitable for image-to-text (captioning) and text-to-image generation tasks.
Dataset Structure
Data Fields
Field
Type
Description
image
Image ({bytes, path} struct)
The face image. Renders in the dataset viewer.
celeb_id
int64
Identity label for the celebrity.
captions… See the full description on the dataset page: https://huggingface.co/datasets/lazarohurtado/celeba-captioned.celeba-faces-captioned
Dataset Card for "celeba-faces-captioned"
More Information needed
celebA_LLaVAceleba-spoof-for-face-antispoofing-testcelebahq-captionCelebAHQ_maskCelebA-attrs-20k
CelebA-128x128
CelebA with attrs at 128x128 resolution.
Dataset Information
The attributes are binary attributes. The dataset is already split into train/test/validation sets.
This dataset has been reduced so there's 20k train samples.
Citation
@inproceedings{liu2015faceattributes,
title = {Deep Learning Face Attributes in the Wild},
author = {Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
booktitle = {Proceedings of International… See the full description on the dataset page: https://huggingface.co/datasets/tpremoli/CelebA-attrs-20k.celeba-smilecelebA_spoof_sample_splitceleba-hq-256x256-metric-refsw2w-celeba-generatedmetacloak_celeba_vggface2
Dataset Card for MetaCloak
Dataset Summary
This repository provides datasets from the MetaCloak.
For each dataset, *-gen is the subset used for protecting, and *-eval is used as a clean reference to calculate some quality metrics.
from datasets import load_dataset
dataset = load_dataset("yixin/metacloak_celeba_vggface2")
Contact
Contact Us: yixinliucs@gmail.com
control-celeba-hq
Dataset Card for Control-CelebA-HQ
Overview
Dataset Name: Control-CelebA-HQDescription: An enhanced version of the CelebA-HQ dataset, Control-CelebA-HQ is specifically designed for evaluating the controlling ability of controllable generative models. This dataset is featured in the NeurIPS 2023 work titled "Controlling Text-to-Image Diffusion by Orthogonal Finetuning (OFT)", and is pivotal in evaluating the control ability of the controllable generative models.Dataset… See the full description on the dataset page: https://huggingface.co/datasets/oftverse/control-celeba-hq.celebahq_512_id_clusters
celebahq_512 with SRK identity labels
Summary
This dataset is a derived version of jxie/celeba-hq. It keeps the original image set and adds automatically generated identity-group labels derived from face-embedding clustering.
As explained in our experimental setup, we use CelebA-HQ from Karras et al. (2018), specifically the Hugging Face snapshot at revision 7ecc6a45edfb5483ccf2f7df1035d298ffe7c76b. The referenced CelebA-HQ version provides gender labels but no identity… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/celebahq_512_id_clusters.cmu-10799-celeba64-subset
CelebA Subset for CMU 10-799
This is a subset of the CelebA dataset[1] for CMU course 10-799 Spring 2026 Diffusion & Flow Matching. This subset is derived from the Kaggle distribution (https://www.kaggle.com/datasets/jessicali9530/celeba-dataset/data).
The images in this subset are filtered by hidden criterias w.r.t. their attributes. The test set is hidden as of now. We preprocess each image by center cropping to the shorter side and then resizing to 64x64 resolution.… See the full description on the dataset page: https://huggingface.co/datasets/electronickale/cmu-10799-celeba64-subset.STGAN_CelebAMMD_GAN_CelebAceleba_with_llava_captions
Dataset Card for "celeba_with_llava_captions"
More Information needed
CelebA-attrs-80k
CelebA-128x128
CelebA with attrs at 128x128 resolution.
Dataset Information
The attributes are binary attributes. The dataset is already split into train/test/validation sets.
This dataset has been reduced so there's 80k train samples.
Citation
@inproceedings{liu2015faceattributes,
title = {Deep Learning Face Attributes in the Wild},
author = {Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
booktitle = {Proceedings of International… See the full description on the dataset page: https://huggingface.co/datasets/tpremoli/CelebA-attrs-80k.celeba_hq_64
CelebA-HQ 64x64
Dataset Description
The 64×64 resolution version of CelebA-HQ, containing 30,000 images.Images are encoded in Base64 format.
Usage
You can refer to the official Parquet tutorial for using the dataset:https://huggingface.co/docs/datasets/v1.12.0/loading.html#parquet
# Load the dataset from Parquet files
base_url = "https://huggingface.co/datasets/BeibeiLim/celeba_hq_64/resolve/main/data/"
data_files = {
"train":… See the full description on the dataset page: https://huggingface.co/datasets/BeibeiLim/celeba_hq_64.CelebA_RoBERTa_Sp
Corpus Summary
This corpus contains 250000 entries made up of a pair of sentences in Spanish and their respective similarity value in the range 0 to 1. This corpus was used in the training of the
sentence-transformer library to improve the efficiency of the RoBERTa-large-bne base model.
Each of the pairs of sentences are textual descriptions of the faces of the CelebA dataset, which were previously translated into Spanish. The process followed to generate it was:
First, a… See the full description on the dataset page: https://huggingface.co/datasets/oeg/CelebA_RoBERTa_Sp.Celeba-Identity-AlignedCeleba-Identity-ITWCelebA-attrs-160k
CelebA-128x128
CelebA with attrs at 128x128 resolution.
Dataset Information
The attributes are binary attributes. The dataset is already split into train/test/validation sets.
This dataset has been reduced so there's 160k train samples.
Citation
@inproceedings{liu2015faceattributes,
title = {Deep Learning Face Attributes in the Wild},
author = {Liu, Ziwei and Luo, Ping and Wang, Xiaogang and Tang, Xiaoou},
booktitle = {Proceedings of International… See the full description on the dataset page: https://huggingface.co/datasets/tpremoli/CelebA-attrs-160k.Celeba-Identity-Aligned-512celebaceleba-hq-glasses