Foundation models in tabular deep learning are a new area of focus.Recent research highlighted TabPFNv2's superior performance over traditional methods on small datasets.Full finetuning is found to be the most effective approach for adapting TabPFNv2, improving time-efficiency and effectiveness.Finetuning alters TabPFNv2's internal mechanisms, enhancing similarity accuracy and improving prediction logic.