This is a transformer based classifier with massive pretraining on synthetic datasets and it outperforms boosting classifiers on many benchmarks without the need of more gradient descent steps (the forward pass on X_train, y_train IS the training).
I understand that jev focus on text entry. But I feel that it is a similar kind of model but trained on text. Did someone test it on tabular data as well ?
This is a transformer based classifier with massive pretraining on synthetic datasets and it outperforms boosting classifiers on many benchmarks without the need of more gradient descent steps (the forward pass on X_train, y_train IS the training).
I understand that jev focus on text entry. But I feel that it is a similar kind of model but trained on text. Did someone test it on tabular data as well ?