Datasets
Hugging FaceDatasets is a lightweight Hugging Face library providing one-line dataloaders for thousands of public datasets and efficient preprocessing for machine-learning workflows. It supports CSV, JSON, Parquet, audio, image and video formats with streaming and memory-mapping, and integrates with PyTorch, TensorFlow and JAX. It is the loading layer that feeds training and evaluation pipelines.
Verified 2026-08-13 via GitHub and the LICENSE body.
Openness
5 high confidence- license
- Apache-2.0(OSI)
- source
- public
- core-gated
- ungated
LICENSE file is the standard, unmodified Apache 2.0 text. The repository is public and unarchived, and the README describes the whole library with no paid, enterprise or hosted tier beside it, so source is public and the core ungated.
- https://github.com/huggingface/datasets/blob/main/LICENSE recorded 2026-08-13
LICENSE file is the verbatim Apache License Version 2.0 text
- https://api.github.com/repos/huggingface/datasets recorded 2026-08-13
Repo metadata - license spdx_id Apache-2.0, private false, archived false, default branch main - for huggingface/datasets.
- https://raw.githubusercontent.com/huggingface/datasets/main/README.md recorded 2026-08-13
README describes one-line dataloaders and efficient preprocessing across formats and modalities. No paid tier or feature-gated build appears.
Adoption
5 high confidence159,958,389 PyPI downloads of `datasets` in the trailing 30 days, which falls in the top band of the software usage scale, over 10M a month, level 5.
- https://pypistats.org/api/packages/datasets/recent recorded 2026-08-13
last_month downloads = 159,958,389 for datasets
Capability
4 high confidenceBroad and central to data pipelines but scoped to data handling rather than modeling.
- https://github.com/huggingface/datasets recorded 2026-08-13
README still describes one-line dataloaders and efficient preprocessing across text, image, audio, video and 3D medical data with streaming
Verified 2026-08-13