Finetuning LLMs with LoRA and QLoRA: Insights from Hundreds of Experiments

LoRA is one of the most widely used, parameter-efficient finetuning techniques for training custom LLMs. From saving memory with QLoRA to selecting the optimal LoRA settings, this article provides practical insights for those interested in applying it.

Related Keywords

,A Good Base Model ,Low Rank Adaptation ,With Low Rank Adaptation ,Good Base ,Rate Schedulers ,Dataset Multiple ,Tuning Part ,Very Large ,Gradient Accumulation ,Normal Float ,