dholzmueller/pytabkit

A Living Benchmark for Machine Learning on Tabular Data

A comprehensive toolkit and benchmark for tabular data learning, featuring 35+ deep methods, more than 10 classical methods, and 300 diverse tabular datasets.

DeepTab is a Python package that simplifies tabular deep learning by providing a suite of models for regression, classification, and distributional regression tasks. It includes models such as Mambular, TabM, FT-Transformer, TabulaRNN, TabTransformer, and tabular ResNets.

TabICLv2: An open tabular foundation model

TabSTAR: A Tabular Foundation Model for Tabular Data with Text Fields

(ICML 2026) TabPack: Efficient Hyperparameter Ensembles for Tabular Deep Learning

A Playground for Tabular Foundation Models

A unified framework for Deep Learning Models on tabular data