ColossalAI

Why we included this project

Colossal-AI is a system-level toolkit for teams that need to train or fine-tune very large models without owning a massive GPU cluster. It packages the hard parts of distributed training, including data, tensor, pipeline, and sequence parallelism plus ZeRO-style optimizer sharding, behind a Python API that plugs into PyTorch. That means a small team can spread a model across many GPUs without writing a lot of custom infrastructure code. It also ships memory-saving techniques like activation offloading and low-precision computation to fit bigger models on the hardware you already have, and it includes inference support for serving the finished models. The project is well documented, with examples and a paper, so it works as a production-grade starting point for engineers who are new to multi-GPU training.