Aiconomy

LoRA (Low-Rank Adaptation)

A parameter-efficient fine-tuning technique that adds small trainable matrices to a frozen pre-trained model, enabling customization with a fraction of the compute and memory normally required.

LoRA, introduced by Microsoft researchers in 2021, typically trains only 0.1-1% of a model's parameters while achieving performance close to full fine-tuning. This reduces GPU memory requirements by up to 3x and training costs by 10-100x. LoRA has become the most popular method for customizing open-source LLMs like Llama and Mistral. Variants like QLoRA combine LoRA with quantization to fine-tune 65-billion-parameter models on a single 48GB GPU — a task that would otherwise require multiple high-end GPUs.

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