AI Potluck
Infrastructure / Core ML frameworks & libraries

Transformers

Hugging Face

Transformers is a model-definition framework for machine learning across text, vision, audio and multimodal models, covering both inference and training. Maintained by Hugging Face, it provides a unified API to load and run over a million pretrained checkpoints from the Hugging Face Hub, and is the interface most published model weights are consumed through.

Verified 2026-08-13 via GitHub and the LICENSE body.

Openness

5 high confidence
5.0
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. The README's only 'Enterprise' string links to the separate Hugging Face Enterprise Hub subscription rather than a feature withheld from this library.

Adoption

5 high confidence
5.0

192,709,895 PyPI downloads of `transformers` in the trailing 30 days, which falls in the top band of the software usage scale, over 10M a month, level 5.

Capability

5 high confidence
5.0

Centralizes model definitions across training frameworks and inference engines; foundational to the ecosystem.

Verified 2026-08-13