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cs.LG2026
FlashOptim: Optimizers for Memory-Efficient Training
Jose Javier Gonzalez Ortiz, Abhay Gupta, Christopher Rinard +1
Standard mixed-precision training of neural networks requires many bytes of accelerator memory for each model parameter. These bytes reflect not just the parameter itself, but also…
cs.LG2024★ 17 cited
LoRA Learns Less and Forgets Less
Dan Biderman, Jacob Portes, Jose Javier Gonzalez Ortiz +9
Low-Rank Adaptation (LoRA) is a widely-used parameter-efficient finetuning method for large language models. LoRA saves memory by training only low rank perturbations to selected w…