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huggingface/datasets

A lightweight library providing one-line dataloaders and efficient pre-processing tools for a vast hub of AI datasets, supporting various ML frameworks.

Core Features

One-line dataloaders for a vast hub of public AI datasets.

Efficient and reproducible data pre-processing for public and local datasets.

Handles large datasets by memory-mapping with Apache Arrow, overcoming RAM limitations.

Seamless interoperability with major ML frameworks like PyTorch, TensorFlow, and JAX.

Native support for diverse data types including audio, image, and video.

Quick Start

pip install datasets

Detailed Introduction

Hugging Face Datasets is a pivotal open-source library designed to streamline the access and manipulation of datasets for artificial intelligence models. It offers a comprehensive hub of ready-to-use public datasets, enabling developers and researchers to load and prepare data with simple, one-line commands. Beyond easy access, the library provides robust and efficient tools for data pre-processing, supporting both public and local datasets across various formats. Built on Apache Arrow, it excels in handling large datasets by memory-mapping, effectively bypassing RAM limitations. With smart caching, transparent APIs, and native interoperability with leading ML frameworks like PyTorch, TensorFlow, and JAX, Hugging Face Datasets empowers the AI community to build, train, and evaluate models more efficiently and reproducibly.