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Train Wide, Deploy Narrow: LoRA Rank Does Not Have to Be One Decision

TL;DR for operators A production team may want every LoRA adapter to fit a small, uniform serving footprint. The usual response is to choose that small rank before training and optimize inside the resulting constraint. This paper shows that the training capacity and the deployment capacity do not always need to be identical. ...

September 5, 2026 · 7 min · Zelina

PaliGemma 2

A next-generation vision-language model by Google, combining Gemma LLM and SigLIP vision encoder for image captioning, VQA, and image-text reasoning tasks.

1 min