QLoRA

LoRA Fine-Tuning Explained: Adapt LLMs for Less

Full fine-tuning of a large language model demands hardware that few teams own. A 175B parameter model needs around 1.2TB of training VRAM with Adam, a figure that puts full fine-tuning out of reach for most developers and small teams. LoRA changes that math. It adapts a model by training a tiny set of extra […]