Transformers

license

Apache-2.0(OSI)

source

public

core features withheld

no

The library is licensed under Apache-2.0 and its source is public. The README describes the whole library with no paid, enterprise or hosted tier beside it, so nothing in the core is withheld.

• https://github.com/huggingface/transformers/blob/main/LICENSE recorded 2026-08-13

  LICENSE file is the verbatim Apache License Version 2.0 text

• https://pypi.org/pypi/transformers/json recorded 2026-09-29

  PyPI metadata for transformers lists the license as "Apache 2.0 License", and the embedded README opens with "Licensed under the Apache License, Version 2.0". It tells readers to "Install Transformers from source" with "git clone https://github.com/huggingface/transformers.git", so the source is public. The README describes the whole library, "Transformers acts as the model-definition framework for state-of-the-art machine learning", and its only Enterprise reference is an image link to "https://huggingface.co/enterprise", the separate Hugging Face Enterprise Hub. Searched the README for paid, pro tier, license key, open source and self-host: no library feature is withheld.

Adoption is measured as PyPI downloads of the transformers package in the trailing 30 days.

• https://pypistats.org/api/packages/transformers/recent recorded 2026-08-13

  last_month downloads = 192,709,895 for transformers

Transformers centralizes model definitions so that training frameworks, inference engines and adjacent libraries can share them, and it supplies pipelines, a trainer and text generation on top. This makes it foundational to the open model ecosystem.

• https://github.com/huggingface/transformers recorded 2026-08-13

  README still describes the model-definition framework for text, vision, audio, video and multimodal models, for inference and training

• https://huggingface.co/docs/transformers/en/index recorded 2026-09-29

  The Transformers documentation home says "Transformers acts as the model-definition framework for state-of-the-art machine learning models in text, computer vision, audio, video, and multimodal models, for both inference and training."

• https://pypi.org/pypi/transformers/json recorded 2026-09-29

  The PyPI README states "Transformers acts as the model-definition framework for state-of-the-art machine learning with text, computer" vision, audio, video and multimodal models, and that "There are over 1M+ Transformers [model checkpoints]" on the Hub.