tft-torch

tft-torch is a Python library that implements the model presented in the paper Temporal Fusion Transformers for Interpretable Multi-horizon Time Series Forecasting by Bryan Lim, Sercan O. Arik, Nicolas Loeff and Tomas Pfister.

The library is implemented using PyTorch framework, and it provides a complete implementation of a time-series multi-horizon forecasting model with state-of-the-art performance on several benchmark datasets.

This library works for Python 3.7 and higher and PyTorch 1.6.0 and higher.

tft-torch also provides detailed documentation and tutorials in order to help and guide users in running experiments using the implemented model.

Note

tft-torch is a python library that can be directly used by data scientists when imported in Jupyter Notebook or Python projects.

For more information, refer to our blogpost.