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The Hugging Face page on cheap tuning says these methods train only a small adapter, not the whole model. That extra piece is usually a LoRA. It cuts the compute and storage cost, and lets big models be trained on ordinary hardware. The model's own numbers are left alone, which is why a free notebook is enough. One documented run, from Google's own LoRA tutorial, read on 14 Sep 2026. It tunes Gemma 3 1B on a Colab T4 at LoRA rank 4. One pass over 1,000 examples, batch size 1, inputs cut at 256 tokens. That pass took 923 seconds, about 15 minutes. The tutorial shows replies before and after, not a score, so the kept-aside score is yours to add.