Informer is a deep learning model that extends the transformer architecture specifically for long sequence time-series forecasting. It introduces ProbSparse self-attention to handle the quadratic computational complexity of standard self-attention, enabling efficient processing of extended sequences. The repository provides the complete PyTorch implementation including model architecture, training procedures, and benchmark datasets for reproducible research.