Accelerate
Hugging FaceAccelerate is a Hugging Face PyTorch library that runs raw PyTorch training scripts across CPUs, multiple GPUs and TPUs with mixed precision, adding only a few lines of code. It abstracts the boilerplate of distributed setup and device placement while leaving the training loop under the caller's control, and provides a CLI for configuration.
Openness
5 high confidence- license
- Apache-2.0(OSI)
- source
- public
- core features withheld
- no
The LICENSE file contains the standard, unmodified Apache 2.0 text. The repository is public and active, and the README describes the full library without a separate paid, enterprise or hosted tier. The source is public and the core is ungated.
- https://github.com/huggingface/accelerate/blob/main/LICENSE recorded 2026-10-06
LICENSE file is the verbatim Apache License Version 2.0 text
- https://huggingface.co/docs/accelerate/basic_tutorials/install recorded 2026-10-06
Install guide gives "pip install git+https://github.com/huggingface/accelerate" and says "an editable version can be installed from a locally-cloned version of the repository".
- https://pypi.org/pypi/accelerate/json recorded 2026-10-06
PyPI metadata for accelerate carries the classifier "License :: OSI Approved :: Apache Software License" and the bundled README opens with "Licensed under the Apache License, Version 2.0".
- https://pypi.org/pypi/accelerate/json recorded 2026-10-06
PyPI package README says "Accelerate abstracts exactly and only the boilerplate code related to multi-GPUs/TPU/fp16" and describes the whole library and its CLI. Searched the body for enterprise, pricing, paid, subscription and license key: none.
Adoption
5 high confidenceAdoption is measured by PyPI downloads of the accelerate package. It is the standard distributed-training launcher across the Hugging Face stack, and libraries such as TRL and PEFT depend on it directly, so its download volume reflects structural use across the ecosystem rather than end-user experimentation alone.
- https://pepy.tech/projects/accelerate recorded 2026-08-13
27,451,175 downloads in the last 30 days for accelerate
Capability
4 high confidenceCentral infrastructure for distributed training but scoped to orchestration, not modeling.
- https://github.com/huggingface/accelerate recorded 2026-08-31
README still describes running raw PyTorch training across CPU, multi-GPU and TPU with mixed precision from a few lines of change
- https://raw.githubusercontent.com/huggingface/accelerate/main/README.md recorded 2026-10-07
README: Accelerate "was created for PyTorch users who like to write the training loop of PyTorch models" and "abstracts exactly and only the boilerplate code related to multi-GPUs/TPU/fp16 and leaves the rest of your code unchanged."
Verified 2026-09-24