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PyTorch Lightning reduces the engineering boilerplate and resources required to implement state-of-the-art AI. Organizing PyTorch code with Lightning enables seamless training on multiple GPUs, TPUs, CPUs as well as the use of difficult to implement best practices such as model sharding, 16-bit precision, and more, without any code changes. In this talk, we will start with a general overview of Deep Learning and then transition into practical Lightning examples to demonstrate how to train Deep Learning models with less boilerplate.
Research Engineer at Lightning AI
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