#lora
2 papers
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inspiration
The Adapter Is Not the Model
The obvious way to serve ten fine-tuned variants is to run ten models. That is wrong. A LoRA adapter is a thin correction on top of a base model — and the base model is the same for all of them. Merging the adapter back into the weights before serving discards the one fact that makes multi-tenant fine-tuning cheap.
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inspiration
LoRA Is Not Fine-Tuning
LoRA does not update your model. It adds a thin, low-rank correction on top — and that distinction changes how you think about deployment, switching, and scale.