Glossary · Math & training
QLoRA
A parameter-efficient fine-tuning method that keeps a pretrained base model frozen in a low-bit quantized representation while training LoRA adapters with higher-precision computation where needed.
Why it matters
It can reduce the memory needed to adapt large models, but savings and quality depend on model, rank, optimizer, sequence length, hardware, and implementation.
Common confusion
QLoRA does not guarantee a particular memory footprint or a fixed quality gap from full fine-tuning.
Related terms
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