Configure parameter-efficient fine-tuning (LoRA/QLoRA) with the right hyperparameters for your model, data, and hardware.
## CONTEXT Parameter-efficient fine-tuning (PEFT) with LoRA or QLoRA makes fine-tuning affordable on modest hardware, but the configuration knobs (rank, alpha, target modules, learning rate, quantization) heavily affect results. In 2026 most fine-tunes use PEFT, and getting the config right is the difference between a…
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