TabM is a tabular deep learning method developed by Yandex Research that introduces parameter-efficient ensembling to improve performance on structured/tabular data. The repository includes a Python package implementing the model along with paper-related code and experiments. It has demonstrated competitive results on real-world industrial benchmarks and has been used in winning Kaggle competition solutions.