QLoRA (Quantization-aware Low-Rank Adaptation) is an efficient fine-tuning approach that reduces memory usage by quantizing a pre-trained language model to 4-bit precision and then fine-tuning only a small number of Low-Rank Adapters (LoRA). This allows large language models to be fine-tuned on a single GPU.
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