In short
Low-Rank Adaptation freezes the base model and trains small injected low-rank matrices instead; QLoRA adds quantization to fine-tune large models on consumer GPUs.
How to learn this
- 1Fine-tune a small open-weight model with LoRA using the Hugging Face `peft` library.
- 2Learn the key LoRA hyperparameters: rank, alpha, target modules.
- 3Try QLoRA on a larger model to see how quantization enables fine-tuning on limited hardware.
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