In this repository you can find the pytorch implementation of the paper Axial LOB: High Frequency Trading with Axial Attention by Damian Kisiel and Denise Gorse.
In the notebook is presented a comprehensive machine learning pipeline that encompasses loading the dataset, applying labeling methods, creating datasets and dataloaders, and ultimately, executing the training, validation, and testing processes.
To run the code you just have to download the FI-2010 dataset and change the data path, then the notebook will do the rest, including the training and testing.