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. Introduction In this article, we will be exploring 9 easily-accessible techniques to reduce memory usage … Continue reading Optimizing Memory Usage for Training LLMs and Vision Transformers in PyTorch