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Lightning AI Announces Availability Compiler for PyTorch - High-Performance Computing News Analysis

New York – March 28, 2024 – Lightning AI today announced the availability of Thunder, a source-to-source compiler for PyTorch designed for training and [.]

New yorkUnited statesChristian sarofeenThomas viehmannLuca antigaNeural network libraryLightning studiosLightning studioDeep learning frameworks

Lightning Studio, An IOS For AI Development?

Lightning AI, the company behind the widely-used PyTorch Lightning framework, has announced the availability of Lightning Studio, to streamline the development and dep.

Christian sarofeenThomas viehmannLightning studioPytorch lightningDeep learning frameworksLightning ai

Lightning AI Announces Availability of Thunder; A Powerful Source-to-Source Compiler For PyTorch That Speeds Up Training And Serving Generative AI Models Across Multiple GPUs, Built With Support From NVIDIA

Lightning AI Announces Availability of Thunder; A Powerful Source-to-Source Compiler For PyTorch That Speeds Up Training And Serving Generative AI Models Across Multiple GPUs, Built With Support From NVIDIA
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Christian sarofeenLuca antigaThomas viehmannNeural network libraryBuilt with support fromPytorch lightningBusiness wireLightning studiosLightning studioDeep learning frameworksPytorch lightningStable diffusion

Improving LoRA: Implementing Weight-Decomposed Low-Rank Adaptation (DoRA) from Scratch

This article implements LoRA (low-rank adaptation), an parameter-efficient finetuning technique for LLMs from scratch and discussed the newest and most promising variant: DoRA (Weight-Decomposed Low-Rank Adaptation).

Weight decomposed low rank adaptationLarge language modelLightning studioImplement low rank adaptationSimple reparameterizationAccelerate trainingDeep neural networksPractical tipsLow rank adaptationPytorch lightning studio