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Infrastructure / Core ML frameworks & libraries

Accelerate

Hugging Face

Accelerate is a Hugging Face PyTorch library that lets users run raw PyTorch training scripts across CPUs, multi-GPU, and TPU configurations with mixed precision, by adding only a few lines of code. It abstracts the boilerplate of distributed setup and device placement while leaving the training loop under the user's control, and provides a CLI for configuration. It is widely used as the distributed-training backbone for other Hugging Face libraries.

Verified live 2026-06-22 via primary sources. LICENSE file is the standard, unmodified Apache 2.0 text.

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.

Adoption

5 high confidence
5.0

Re-scored 4->5. 25.01M PyPI downloads in the last 30 days. The map's prevailing usage_volume level-5 floor is >10M/mo (cf. pydantic-ai ~31M, llama-index ~10.18M at level 5); the prior note bucketed it into a 5M-50M=L4 band used only in one ml_frameworks batch, below map peers of equal volume. Accelerate is the standard distributed-training launcher under the HF stack (TRL/PEFT depend on it) and clears the prevailing floor.

Capability

4 high confidence
4.0

Central infrastructure for distributed training but scoped to orchestration, not modeling.

Unchanged since 2026-07-30 (last edited, not re-checked)