TabFM Brings Zero‑Shot Prediction to Tabular Data
TabFM is Google Research’s new foundation model that predicts on tabular classification and regression tasks without any per‑dataset training, hyperparameter tuning, or manual feature engineering. It leverages in‑context learning (ICL) with a hybrid attention architecture and is pretrained on hundreds of millions of synthetic tables. Benchmarks on the TabArena suite show TabFM (both default and ensemble variants) achieving higher Elo scores than heavily tuned traditional models.