datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
cifar10
Dataset Card for CIFAR-10
Dataset Summary
The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.
The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may contain… See the full description on the dataset page: https://huggingface.co/datasets/uoft-cs/cifar10.cifar100
Dataset Card for CIFAR-100
Dataset Summary
The CIFAR-100 dataset consists of 60000 32x32 colour images in 100 classes, with 600 images
per class. There are 500 training images and 100 testing images per class. There are 50000 training images and 10000 test images. The 100 classes are grouped into 20 superclasses.
There are two labels per image - fine label (actual class) and coarse label (superclass).
Supported Tasks and Leaderboards
image-classification: The… See the full description on the dataset page: https://huggingface.co/datasets/uoft-cs/cifar100.cifar100-enrichedThe CIFAR-100 dataset consists of 60000 32x32 colour images in 100 classes, with 600 images
per class. There are 500 training images and 100 testing images per class. There are 50000 training images and 10000 test images. The 100 classes are grouped into 20 superclasses.
There are two labels per image - fine label (actual class) and coarse label (superclass).cifar10
Dataset Card for CIFAR-10
Dataset Summary
The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.
The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may contain… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cifar10.TTA-CIFAR-100-C
TTA-CIFAR-100-C
Mirror of CIFAR-100-C (Hendrycks & Dietterich, ICLR 2019) with a
revision pin for reproducible test-time adaptation evaluation.
Upstream: Zenodo record 3555552
License: CC BY 4.0 (matches upstream)
Sibling: TTA-CIFAR-10-C
Maintained as part of: TTA-Evaluation-Harness
Citation
@inproceedings{hendrycks2019benchmarking,
title={Benchmarking Neural Network Robustness to Common Corruptions and Perturbations},
author={Hendrycks, Dan and Dietterich… See the full description on the dataset page: https://huggingface.co/datasets/WNJXYK/TTA-CIFAR-100-C.cifar100-lt
Dataset Card for CIFAR-100-LT (Long Tail)
Dataset Summary
Note (March 2026): This dataset has been migrated from a Python loading script to
parquet format for compatibility with datasets v4.4+. No trust_remote_code=True
is needed. Available configs: r-10, r-20, r-50, r-100.
The CIFAR-100-LT imbalanced dataset is comprised of under 60,000 color images, each measuring 32x32 pixels,
distributed across 100 distinct classes.
The number of samples within each class… See the full description on the dataset page: https://huggingface.co/datasets/tomas-gajarsky/cifar100-lt.TTA-CIFAR-10-C
TTA-CIFAR-10-C
Mirror of CIFAR-10-C (Hendrycks & Dietterich, ICLR 2019) with a revision
pin for reproducible test-time adaptation evaluation.
Upstream: Zenodo record 2535967
License: CC BY 4.0 (matches upstream)
SHA256 of upstream tarball: c72763e101c723b7c507b96205f7e938912a5d587376173b825850cf3cb876a7
Maintained as part of: TTA-Evaluation-Harness
Citation
@inproceedings{hendrycks2019benchmarking,
title={Benchmarking Neural Network Robustness to Common… See the full description on the dataset page: https://huggingface.co/datasets/WNJXYK/TTA-CIFAR-10-C.cifar10-lt
Dataset Card for CIFAR-10-LT (Long Tail)
Dataset Summary
Note (March 2026): This dataset has been migrated from a Python loading script to
parquet format for compatibility with datasets v4.4+. No trust_remote_code=True
is needed. Available configs: r-10, r-20, r-50, r-100.
The CIFAR-10-LT imbalanced dataset is comprised of under 60,000 color images, each measuring 32x32 pixels,
distributed across 10 distinct classes.
The number of samples within each class decreases… See the full description on the dataset page: https://huggingface.co/datasets/tomas-gajarsky/cifar10-lt.cifar10
Dataset Specifications
Contains the entire CIFAR10 dataset, downloaded via PyTorch, then split and saved as .png files representing 32x32 images.
There a three splits, perfectly balanced class-wise:
train: 49,000 out of the original 50,000 samples from the training set of CIFAR10;
calibration: 1,000 left-out samples from the training set;
test: 10,000 samples, the entire original test set.
File Structure
Files are archives <split>/<classname>.zip. Each… See the full description on the dataset page: https://huggingface.co/datasets/ego-thales/cifar10.CIFAR10
🖼️ CIFAR10 (Extracted from PyTorch Vision)
The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.
ℹ️ Dataset Details
📖 Dataset Description
The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images. The classes are completely mutually exclusive. There is no… See the full description on the dataset page: https://huggingface.co/datasets/p2pfl/CIFAR10.CIFAR-10
CIFAR-10 - Object Recognition in Images
Benchmark dataset for object classification.🖼️ 60,000 32x32 color images🏷️ 10 classes📁 Format: PNG, CSV📦 Files: 4🧪 Subset of the 80 million tiny images dataset
Dataset Summary
CIFAR-10 is a widely used computer vision dataset consisting of 60,000 32x32 color images in 10 mutually exclusive classes. It was created by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton. The dataset is a labeled subset of the 80 million tiny… See the full description on the dataset page: https://huggingface.co/datasets/KDKCE/CIFAR-10.cifar100
Dataset Card for CIFAR-100
Dataset Summary
The CIFAR-100 dataset consists of 60000 32x32 colour images in 100 classes, with 600 images
per class. There are 500 training images and 100 testing images per class. There are 50000 training images and 10000 test images. The 100 classes are grouped into 20 superclasses.
There are two labels per image - fine label (actual class) and coarse label (superclass).
Supported Tasks and Leaderboards
image-classification: The… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cifar100.xai-attack-detection-cifar10
XAI Attack Detection — CIFAR-10 PGD
This private research dataset contains balanced, paired clean and adversarial images for
studying whether an attack can be detected from a classifier explanation map.
Dataset construction
The source is the CIFAR-10 test split. A fine-tuned OpenCLIP ViT-B/16 classifies each
clean image. Clean-correct examples are attacked with untargeted L-infinity PGD using
epsilon 8/255, step size 2/255, 10 steps, and deterministic random… See the full description on the dataset page: https://huggingface.co/datasets/nimaeb/xai-attack-detection-cifar10.cifar10h
CIFAR-10H Hugging Face Dataset
This repository contains a Hugging Face dataset build of CIFAR-10H, an extension of the CIFAR-10 test set with human-annotated label distributions.
Dataset Description
CIFAR-10H adds human uncertainty information to the CIFAR-10 test images by providing:
expert_probs: probability distributions over the 10 CIFAR-10 classes
expert_counts: raw human vote counts for each class
expert_argmax: one-hot encoded labels from the human-majority choice… See the full description on the dataset page: https://huggingface.co/datasets/MKZuziak/cifar10h.cifar10-lance
CIFAR-10 (Lance Format)
A Lance-formatted version of CIFAR-10 covering 60,000 32×32 RGB images across ten balanced object classes. Each row carries inline PNG bytes, the integer label, the human-readable class name, and a cosine-normalized CLIP image embedding, all backed by a bundled IVF_PQ vector index plus scalar indices on the label columns and available directly from the Hub at hf://datasets/lance-format/cifar10-lance/data.
Key features
Inline PNG bytes in the… See the full description on the dataset page: https://huggingface.co/datasets/lance-format/cifar10-lance.cifar100-lt
Dataset Card for CIFAR-100-LT (Long Tail)
Dataset Summary
Note (March 2026): This dataset has been migrated from a Python loading script to
parquet format for compatibility with datasets v4.4+. No trust_remote_code=True
is needed. Available configs: r-10, r-20, r-50, r-100.
The CIFAR-100-LT imbalanced dataset is comprised of under 60,000 color images, each measuring 32x32 pixels,
distributed across 100 distinct classes.
The number of samples within each class… See the full description on the dataset page: https://huggingface.co/datasets/Amanmeena004/cifar100-lt.cifar10
Dataset Card for CIFAR-10
Dataset Summary
The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.
The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may… See the full description on the dataset page: https://huggingface.co/datasets/puneet44/cifar10.CIFAR-10_Subset
CIFAR-10 — Subset
Stratified random subset of CIFAR-10.
Split
Rows
Per class
train
5,000
500
test
1,000
100
validation
500
50
Classes: airplane, automobile, bird, cat, deer, dog, frog, horse, ship, truck
Images: 32 × 32 RGB | Seed: 42
Label Map
ID
Class
ID
Class
0
airplane
5
dog
1
automobile
6
frog
2
bird
7
horse
3
cat
8
ship
4deer
9
truck
Usage
from datasets import load_dataset
ds =… See the full description on the dataset page: https://huggingface.co/datasets/Chiranjeev007/CIFAR-10_Subset.cifar10-outlier
Dataset Card for "cifar10-outlier"
📚 This dataset is an enriched version of the CIFAR-10 Dataset.
The workflow is described in the medium article: Changes of Embeddings during Fine-Tuning of Transformers.
Explore the Dataset
The open source data curation tool Renumics Spotlight allows you to explorer this dataset. You can find a Hugging Face Spaces running Spotlight with this dataset here:
Full Version (High hardware requirement)… See the full description on the dataset page: https://huggingface.co/datasets/renumics/cifar10-outlier.cifar100-outlier
Dataset Card for "cifar100-outlier"
📚 This dataset is an enriched version of the CIFAR-100 Dataset.
The workflow is described in the medium article: Changes of Embeddings during Fine-Tuning of Transformers.
Explore the Dataset
The open source data curation tool Renumics Spotlight allows you to explorer this dataset. You can find a Hugging Face Space running Spotlight with this dataset here: https://huggingface.co/spaces/renumics/cifar100-outlier.
Or you can explorer it… See the full description on the dataset page: https://huggingface.co/datasets/renumics/cifar100-outlier.cifar10
Dataset Card for CIFAR-10
Dataset Summary
The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.
The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may contain… See the full description on the dataset page: https://huggingface.co/datasets/Tom-Michae-lDavis/cifar10.cifar10-lt-federated
CIFAR-10 Long-Tail Federated Dataset
Dataset Description
This is a long-tailed version of CIFAR-10 designed for federated learning research. The dataset introduces class imbalance following an exponential decay distribution, making it ideal for studying long-tail classification in federated settings.
Class Distribution (Training Set)
The training set follows a long-tail distribution with imbalance factor 100:
airplane (Class 0): 5,000 samples
automobile (Class… See the full description on the dataset page: https://huggingface.co/datasets/Beothuk/cifar10-lt-federated.cifar10
Dataset Card for CIFAR-10
Dataset Summary
The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.
The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may contain… See the full description on the dataset page: https://huggingface.co/datasets/summerhot12138/cifar10.cifar-10-subset
CIFAR-10 Subset
This dataset contains a subset of the CIFAR-10 image classification dataset.
Dataset Description
A curated subset of the CIFAR-10 dataset useful for demonstrating image classification and data quality techniques without requiring the full dataset.
Usage
# Download the dataset
wget https://huggingface.co/datasets/Cleanlab/cifar-10-subset/resolve/main/CIFAR-10-subset.zip
unzip CIFAR-10-subset.zip
from huggingface_hub import hf_hub_download
#… See the full description on the dataset page: https://huggingface.co/datasets/Cleanlab/cifar-10-subset.cifar10
Dataset Card for CIFAR-10
Dataset Summary
The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.
The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may… See the full description on the dataset page: https://huggingface.co/datasets/superEagele/cifar10.CIFAR100-customExample of usage:
from datasets import load_dataset
dataset = load_dataset("Andron00e/CIFAR100-custom")
splitted_dataset = dataset["train"].train_test_split(test_size=0.2)
CIFAR10-customExample of usage:
from datasets import load_dataset
dataset = load_dataset("Andron00e/CIFAR10-custom")
splitted_dataset = dataset["train"].train_test_split(test_size=0.2)
Cifar10Mnist
Cifar10Mnist Dataset Card
Dataset Summary
Cifar10Mnist is a synthetic image dataset created by overlaying MNIST digit images on top of CIFAR-10 images. Each example contains a 32x32 RGB image and a paired label tuple: the original CIFAR-10 class name plus the MNIST digit label.
Supported Tasks
Image classification
Multi-label classification
Transfer learning
Synthetic data research
Languages
Not language-specific… See the full description on the dataset page: https://huggingface.co/datasets/shotegni/Cifar10Mnist.cifar10
Dataset Card for CIFAR-10
Dataset Summary
The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.
The dataset is divided into five training batches and one test batch, each with 10000 images. The test batch contains exactly 1000 randomly-selected images from each class. The training batches contain the remaining images in random order, but some training batches may… See the full description on the dataset page: https://huggingface.co/datasets/mead99/cifar10.Cifar-ExtendedThese images were generated with an image generator I trained on the CIFAR-10 datasetThere are 250k images in totalNot recommended for serious training, only experimentation
Name Format:
(name)_(counter)(index).png
Name: airplane, automobile, bird, cat, deer, dog, frog, horse, ship, truckCounter: every digit besides the last, range from 0 to 24999Index: each name has one, they range from 0 to 9 (airplane - 0, automobile - 1, bird - 2...)
Example: bird_115102.png (Name - bird, Counter -… See the full description on the dataset page: https://huggingface.co/datasets/ThatHungarian/Cifar-Extended.