0.1.15

🚀 TabTune v0.1.15 Release Update

This release introduces two major new capabilities in TabTune:

1. Distillation Module

TabTune now supports distillation across all supported TFMs, enabling knowledge transfer from transformer-based models into a broad set of student models, including:

• XGBoost
• CatBoost
• LightGBM
• MLP

This makes it easier to build faster, lighter, and more deployment-friendly tabular models while retaining strong predictive performance.

2. Ensembling Module

We have added a new Ensembling Module that allows users to combine TabTune-supported TFMs using six state-of-the-art ensembling strategies.

This provides greater flexibility for improving model robustness, stability, and overall performance across tabular ML tasks.