Individual skill
vision-sft
Fine-tune vision-language models (VLMs) with supervised learning on image+text data. Use when adapting a VLM to a visual domain or task, configuring frozen-vision-tower LoRA, or debugging a VLM fine-tune that trains without learning.
plugins/llm-finetuning/skills/vision-sft/SKILL.md
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# Vision-Language SFT
This skill assumes `finetuning-method-selection`
already routed here: the data shape is
image+text demonstrations, not preference pairs
or a verifiable reward signal, and the base is a
vision-language model rather than a text-only
one. `lora-qlora-recipes` covers the text-only
LoRA/QLoRA recipe this skill specializes for the
vision tower and projector; read that skill first
if the LoRA fundamentals (rank, alpha, target
modules) aren't already familiar.
**Input:** an image+text dataset and a VLM base