README.md

Getting Started: Session-based Recommendation with Synthetic Data

This example notebook focuses on the following basic concepts of Transformers4Rec:

• Generating synthetic data of user interactions.
• Preprocessing sequential data with NVTabular on GPU.
• Using the NVTabular dataloader with PyTorch.
• Training a session-based recommendation model with a Transformer architecture (XLNET).

Refer to the following notebooks:

• ETL with NVTabular
• Session based XLNET: PyTorch