LoRA Fine-Tune

Key Insight

LoRA (Low-Rank Adaptation) is the reason you can teach a giant Stable Diffusion checkpoint a brand-new subject on a single consumer GPU. Instead of fine-tuning all of the model's frozen weights, you leave them untouched and train only a tiny pair of low-rank matrices that nudge each layer's output — so the result is a few megabytes you can share and swap, not a full multi-gigabyte model. The practical lesson of training on ~20 images of a custom subject is the tension between learning the subject and overfitting: too many steps and the model can only ever redraw your training photos, too few and it never locks onto the subject at all.