TabPFN

Deliver a pinned, task-evaluated TabPFN workflow rather than treating a sklearn-like API as proof of compatibility, permission or predictive quality. TabPFN learns a synthetic-data prior during pretraining and conditions on a labeled training table at inference. Its ordinary fit is not necessarily dataset-specific gradient training; explicit fine-tuning is a distinct operation.

When not to use

• For choosing among trees, TabPFN, TabICL, sequence models and LLMs, load ml-engineering.
• For statistical design/calibration, use data-scientist.
• For language-model SFT/LoRA/RL, use unsloth.
• TabICL has different models/APIs and terms. This skill does not operate it.

First decision and authority