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.cifar100cifar-10-ccifar10cif-dataset
Cracks in the Foundation
A civil-infrastructure visual inspection dataset for instance segmentation with 6 defect/condition categories:
Algae · Crack · Net-Crack · Crack with Precipitation · Rust · Spalling
Each sample is either a full-resolution inspection image or a 1024×1024 tile derived from one.
Tiled samples carry extra fields (tile_row, tile_col, file_name_original, …) that are None for full-resolution samples.
Splits
Each split is its own parquet shard and… See the full description on the dataset page: https://huggingface.co/datasets/ibm-research/cif-dataset.cifar100_2_to_100_constant_size_dataset
Dataset Card for "cifar100_2_to_100_constant_size_dataset"
More Information needed
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.msc-cifar100
MSC — Minimum Sufficient Compute
Artifacts for Is Compute Difficulty Architecture-Agnostic? Measuring and
Distilling Per-Sample Minimum Sufficient Computation.
Generated 2026-08-06T03:56:37Z by msc_lib v1.0.0.
Repositories
Shanmuk4622/msc-cifar100 — everything, one folder per run
What MSC is
The smallest cost-normalised configuration at which a network's decision has
stably settled to its full-compute decision, defined uniformly over depth… See the full description on the dataset page: https://huggingface.co/datasets/Shanmuk4622/msc-cifar100.CIFAKE-image-datasetsemasia-cifar100
Latents for cifar100 (timm)
This repository hosts precomputed latent representations (embeddings) extracted from timm image-classification backbones on cifar100, released as part of SEMASIA — a large-scale resource for studying semantic communication, cross-model latent space alignment, and explainability.
Each config corresponds to a single model;
only that model's Parquet files are read on load_dataset.
Usage
Load with datasets and… See the full description on the dataset page: https://huggingface.co/datasets/spaicom-lab/semasia-cifar100.cifar100_2_to_100
Dataset Card for "cifar100_2_to_100"
More Information needed
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.CIFAR10
Dataset Card for CIFAR10
Dataset Summary
The CIFAR10 dataset consists of 45000 images in 10 classes, represented as graphs.
Supported Tasks and Leaderboards
CIFAR10 should be used for multiclass graph classification.
External Use
PyGeometric
To load in PyGeometric, do the following:
from datasets import load_dataset
from torch_geometric.data import Data
from torch_geometric.loader import DataLoader
dataset_hf =… See the full description on the dataset page: https://huggingface.co/datasets/graphs-datasets/CIFAR10.CIFAR10_train
Dataset Card for "CIFAR10_train"
More Information needed
CIFAR10_test
Dataset Card for "CIFAR10_test"
More Information needed
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
🖼️ 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.cif-datasetcifar100
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.cifar10_512x512px
Dataset Card for "cifar10_512x512px"
More Information needed
cif-dataset
Cracks in the Foundation
A civil-infrastructure visual inspection dataset for instance segmentation with 6 defect/condition categories:
Algae · Crack · Net-Crack · Crack with Precipitation · Rust · Spalling
Each sample is either a full-resolution inspection image or a 1024×1024 tile derived from one.
Tiled samples carry extra fields (tile_row, tile_col, file_name_original, …) that are None for full-resolution samples.
Splits
Each split is its own parquet shard… See the full description on the dataset page: https://huggingface.co/datasets/dc881012/cif-dataset.cifar100-clip-featuresupside_down_detection_cifar100erased-cifarnetxai-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.CIFAR100-Blended-20pct-Backdoor-ExclNaturalspotlight-cifar100-enrichment
Dataset Card for "spotlight-cifar100-enrichment"
More Information needed