Sebastian Raschka • 7/1/2023

Optimizing Memory Usage for Training LLMs and Vision Transformers in PyTorch

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This article details 9 cumulative techniques for optimizing memory consumption in PyTorch, applicable to models like Vision Transformers and LLMs. It covers methods such as mixed-precision training, gradient accumulation, and parameter offloading, using the Fabric library to simplify implementation and enable training on consumer hardware.

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#memory optimization #Pytorch #Gradient Accumulation
Optimizing Memory Usage for Training LLMs and Vision Transformers in PyTorch

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