Optimizing Memory Usage for Training LLMs and Vision Transformers in PyTorch

Peak memory consumption is a common bottleneck when training deep learning models such as vision transformers and LLMs. This article provides a series of techniques that can lower memory consumption by approximately 20x without sacrificing modeling performance and prediction accuracy.