ft-transformer

SupraLabs released SupraWeather-Nano-Preview, a small FT-Transformer model for classifying weather phenomena from tabular meteorological features, trained on synthetic data as an architecture experiment.

This paper presents a hybrid architecture combining FT-Transformer with gradient-boosted trees via calibration-aware stacking for customer churn prediction on structured tabular data, achieving improved F1 and AUC-ROC on a public bank churn dataset.