Translated data: Sebastian Raschka shares insights on the use of LoRA technology in fine-tuning large models, emphasizing its cost-effectiveness. QLoRA demonstrates significant performance in memory optimization. The choice of optimizer has minimal impact on the fine-tuning results, while LoRA requires comprehensive application on static datasets, with adjusting the rank and α values being crucial.