Fine-tuning & LoRA
Concept
Training & Inference
Adapting a trained model cheaply — the small-compute on-ramp.
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Fine-tuning continues training on a narrow dataset to specialize a model; LoRA does it by learning tiny low-rank adapter matrices instead of touching all weights, cutting cost by orders of magnitude. It is how enterprises adapt open models, how the Stable Diffusion style ecosystem works, and what products like Tinker sell as a service.
How this connects to the rest of the stack
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Introduced
Based on
Related
Sources
Record reviewed as of 2026-01-15 — see Methodology.