Chris-hughes10/pytorch-accelerated
A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases, and capable of utilizing different hardware options with no code changes required. Docs: https://pytorch-accelerated.readthedocs.io/en/latest/
This project helps machine learning engineers efficiently train their PyTorch models by providing a simplified, yet flexible, training loop. You input your PyTorch model, data, optimizer, and loss function, and it outputs a trained model. It's designed for machine learning engineers who want to streamline their model training workflow without dealing with complex boilerplate code for different hardware setups.
193 stars. Available on PyPI.
Use this if you are a machine learning engineer working with PyTorch and want to quickly train models across various hardware, including multi-GPU or distributed setups, with minimal code changes.
Not ideal if you need a very low-level, highly customized training routine that requires explicit control over every single training step and device interaction without any abstractions.
Stars
193
Forks
19
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 27, 2026
Commits (30d)
0
Dependencies
1
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