We present TabPFN, a trained Transformer model that can do tabular supervised classification for small datasets in less than a second, needs no hyperparameter tuning and is competitive with state-of-the-art classification methods.TabPFN is entailed in the weights of our network, which accepts training and test samples as a set-valued input and yields predictions for the entire test set in a single forward pass. TabPFN is a Prior-Data Fitted Network (PFN) and is trained offline once, to approxim…