Probabilistic Time Series Forecasting with Transformers

Hugging Face Transformers now supports probabilistic time series forecasting using the Time Series Transformer model. This enables global probabilistic modeling, allowing for the prediction of future values along with their uncertainties. The implementation leverages the Encoder-Decoder Transformer architecture, handling sequential data, missing values, and offering ancestral sampling for forecasting. The post details the setup, data loading, model definition, training, and inference processes using the `monash_tsf` dataset and GluonTS for data transformation and batching.