TabICLv2 is a state-of-the-art tabular foundation model published at ICML 2026. It performs classification and regression on tabular data using a pre-trained transformer, achieving top performance on the TabArena and TALENT benchmarks without hyperparameter tuning. It is pip-installable, scikit-learn compliant, and runs inference via a single forward pass with optional GPU acceleration.