QLoRA (Quantized Low-Rank Adaptation) is a technique for fine-tuning large language models on modest hardware. It compresses the base model to 4-bit precision through quantization, then trains only small LoRA adapter layers on top, cutting memory needs dramatically while keeping quality close to full fine-tuning. Thanks to QLoRA, a Moroccan startup can adapt an open-source model to Darija customer messages using a single consumer GPU instead of renting an expensive cluster.