datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
mnist
Dataset Card for MNIST
Dataset Summary
The MNIST dataset consists of 70,000 28x28 black-and-white images of handwritten digits extracted from two NIST databases. There are 60,000 images in the training dataset and 10,000 images in the validation dataset, one class per digit so a total of 10 classes, with 7,000 images (6,000 train images and 1,000 test images) per class.
Half of the image were drawn by Census Bureau employees and the other half by high school students… See the full description on the dataset page: https://huggingface.co/datasets/ylecun/mnist.fashion_mnist
Dataset Card for FashionMNIST
Dataset Summary
Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes. We intend Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing… See the full description on the dataset page: https://huggingface.co/datasets/zalando-datasets/fashion_mnist.semasia-mnist
Latents for mnist (timm)
This repository hosts precomputed latent representations (embeddings) extracted from timm image-classification backbones on mnist, 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 convert to… See the full description on the dataset page: https://huggingface.co/datasets/spaicom-lab/semasia-mnist.MNIST-M
Train Example
👉Domain-Adversarial-Neural-Network
MNIST
🖼️ MNIST (Extracted from PyTorch Vision)
MNIST is a classic dataset of handwritten digits, widely used for image classification tasks in machine learning.
ℹ️ Dataset Details
📖 Dataset Description
The MNIST database of handwritten digits is a commonly used benchmark dataset in machine learning. It consists of 70,000 grayscale images of handwritten digits (0-9), each with a size of 28x28 pixels. The dataset is split into 60,000 training images and 10,000… See the full description on the dataset page: https://huggingface.co/datasets/p2pfl/MNIST.mnistsemasia-fashion_mnist
Latents for fashion_mnist (timm)
This repository hosts precomputed latent representations (embeddings) extracted from timm image-classification backbones on fashion_mnist, 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… See the full description on the dataset page: https://huggingface.co/datasets/spaicom-lab/semasia-fashion_mnist.tactile-mnist-touch-syn-single-t32-320x240Documentation is available at https://github.com/TimSchneider42/tactile-mnist/blob/main/doc/datasets.md#touch-datasets.
tactile-mnist-mnist3dDocumentation is available at https://github.com/TimSchneider42/tactile-mnist/blob/main/doc/datasets.md#3d-mesh-datasets.
emnist_mnist
Dataset Card for "emnist-mnist"
Dataset Information
The emnist-mnist dataset is a set of images of handwritten digits. The dataset is split into a training set and a test set.
Data Fields
image: The image of the handwritten digit. The data type of this field is image.
label: The label of the handwritten digit. The data type of this field is class_label, and it can take on the values '0' to '9'.
Data Splits
train: The training set consists of 60000… See the full description on the dataset page: https://huggingface.co/datasets/tanganke/emnist_mnist.vdf_PC_ANN_Fashion-MNIST_d784_euclideanThis is a dataset created using vector-io
tactile-mnist-touch-starstruck-syn-single-t32-320x240Documentation is available at https://github.com/TimSchneider42/tactile-mnist/blob/main/doc/datasets.md#touch-datasets.
mnist1d
[!NOTE]
This dataset card is based on the README file of the authors' GitHub repository: https://github.com/greydanus/mnist1d
The MNIST-1D Dataset
Most machine learning models get around the same ~99% test accuracy on MNIST. The MNIST-1D dataset is 100x smaller (default sample size: 4000+1000; dimensionality: 40) and does a better job of separating between models with/without nonlinearity and models with/without spatial inductive biases.
MNIST-1D is a core teaching dataset in… See the full description on the dataset page: https://huggingface.co/datasets/christopher/mnist1d.mnist-world
MNIST World Dataset
This repository contains the MNIST World dataset, used for experiments in the paper Flow Equivariant World Models: Memory for Partially Observed Dynamic Environments, accepted at ICML 2026.
MNIST World is a 2D partially observed video world modeling benchmark designed to evaluate how well models can handle smooth, time-parameterized symmetries and unobserved regions that continue to evolve.
Project Resources
Paper: arXiv:2601.01075
Project… See the full description on the dataset page: https://huggingface.co/datasets/flowm123/mnist-world.tactile-mnist-touch-real-seq-t256-320x240Documentation is available at https://github.com/TimSchneider42/tactile-mnist/blob/main/doc/datasets.md#touch-datasets.
MNIST
Dataset Card for MNIST
Dataset Summary
The MNIST dataset consists of 55000 images in 10 classes, represented as graphs. It comes from a computer vision dataset.
Supported Tasks and Leaderboards
MNIST 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… See the full description on the dataset page: https://huggingface.co/datasets/graphs-datasets/MNIST.capstone_captioned_moving_mnist_framesaudio-MNIST
This dataset only contains test data, which is integrated into UltraEval-Audio(https://github.com/OpenBMB/UltraEval-Audio) framework.
python audio_evals/main.py --dataset audio-MNIST --model gpt4o_audio
🚀超凡体验，尽在UltraEval-Audio🚀
UltraEval-Audio——全球首个同时支持语音理解和语音生成评估的开源框架，专为语音大模型评估打造，集合了34项权威Benchmark，覆盖语音、声音、医疗及音乐四大领域，支持十种语言，涵盖十二类任务。选择UltraEval-Audio，您将体验到前所未有的便捷与高效：
一键式基准管理 📥：告别繁琐的手动下载与数据处理，UltraEval-Audio为您自动化完成这一切，轻松获取所需基准测试数据。
内置评估利器… See the full description on the dataset page: https://huggingface.co/datasets/TwinkStart/audio-MNIST.RGB-MNISTmnist
Dataset Card for MNIST
Dataset Summary
The MNIST dataset consists of 70,000 28x28 black-and-white images of handwritten digits extracted from two NIST databases. There are 60,000 images in the training dataset and 10,000 images in the validation dataset, one class per digit so a total of 10 classes, with 7,000 images (6,000 train images and 1,000 test images) per class.
Half of the image were drawn by Census Bureau employees and the other half by high school students… See the full description on the dataset page: https://huggingface.co/datasets/mteb/mnist.galaxy_mnist
Dataset GZMNIST
Dataset create from Mike Walmsley repo : https://github.com/mwalmsley/galaxy_mnist
Contains 10,000 images of galaxies, only HiRes 3x224x224.
Confidently labelled by Galaxy Zoo volunteers as belonging to one of four morphology classes.
Classes
0 : 'smooth and round'
1 : 'smooth and cigar-shaped'
2 : 'edge-on-disk'
3 : 'unbarred spiral
Data from / Citation :
Walmsley et al.(2022) - 2022MNRAS.509.3966W
Walmsley, M. and 17 colleagues 2022.
Galaxy… See the full description on the dataset page: https://huggingface.co/datasets/matthieulel/galaxy_mnist.capstone_captioned_moving_mnist_t5_embeddingsfashion-mnist-784-euclidean
Dataset Overview
dataset: fashion-mnist-784-euclidean
Metadata
Creation Time: 2025-01-07 11:02:55+0000
Update Time: 2025-01-07 11:03:01+0000
Source: https://github.com/erikbern/ann-benchmarks
Task: N/A
Train Samples: N/A
Test Samples: N/A
License: DISCLAIMER AND LICENSE NOTICE:
This dataset is intended for benchmarking and research purposes only.
The source data used in this dataset retains its original license and copyright. Users must comply with the respective… See the full description on the dataset page: https://huggingface.co/datasets/open-vdb/fashion-mnist-784-euclidean.tactile-mnist-wrenchDocumentation is available at https://github.com/TimSchneider42/tactile-mnist/blob/main/doc/datasets.md#3d-mesh-datasets.
tactile-mnist-abc-dataset-small
ABC Dataset
Meshes from the ABC dataset processed for use in the Tactile MNIST Benchmark Suite.
Specifically, meshes were first filtered, including only those that
Fit in a cuboid of width 100 mm and height 50 mm
Are at least 1mm wide and 1 mm tall
Have a volume of at least 1000 mm³
Moreover, meshes were simplified to have at most 500 faces per cm² of their surface area via trimesh's simplify_quadratic_decimation method.
Find usage documentation here and the full dataset here.… See the full description on the dataset page: https://huggingface.co/datasets/TimSchneider42/tactile-mnist-abc-dataset-small.difficult_mnist_2ylecun-mnistfashion-mnisttactile-mnist-abc-dataset
ABC Dataset
Meshes from the ABC dataset.
For the metadata, refer to the metadata dataset.
The full dataset is available at the dataset's website.
License
Note that I am not the creator of the ABC dataset; hence, I hold no copyright over it.
The copyright of the CAD models is owned by their creators.
For licensing details, see Onshape Terms of Use 1.g.ii.
This version of the dataset does not contain any metadata.
Hence, to identify the creator of a specific model, please… See the full description on the dataset page: https://huggingface.co/datasets/TimSchneider42/tactile-mnist-abc-dataset.fashion_mnist
Dataset Card for FashionMNIST
Dataset Summary
Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes. We intend Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing… See the full description on the dataset page: https://huggingface.co/datasets/anonyme449/fashion_mnist.