ACCELERATE
Run raw PyTorch training on any device configuration
ABOUT
Writing distributed training code for PyTorch is a swamp of boilerplate: setting up process groups, handling gradient accumulation, managing device placement, configuring mixed precision, and integrating with DeepSpeed or FSDP. Each of these has its own API and gotchas, and getting them wrong silently corrupts training or wastes GPUs. Accelerate abstracts all of this into a single Accelerator class. You write standard PyTorch training loops, add one line — accelerator = Accelerator() — and suddenly your script runs on single GPU, multi-GPU, multi-node, TPU, or mixed precision without any code changes. This is essential infrastructure for fine-tuning LLMs and large models where distributed training is non-negotiable.
pip install accelerate