Show HN: T0: We trained a 256M SOTA open-weights time-series forecasting model

Hi everyone, we are excited to share t0-gamma, the latest model in our t0 family. It is a 256M parameter open-weights foundation model for time series (TSFM). It runs on CPU, GPU or Apple chips. https://huggingface.co/theforecastingcompany/t0-gamma t0 leverages historical data to forecast the likely outcomes over a given horizon. It does so zero-shot. It works on almost any time series, as it can pick up small signals like trends and seasonality. It can also leverage future-known information, like holidays, promotions and weather forecasts. Under the hood, t0 is a transformer that alternates attention between time and across the variates of a series. t0 is agnostic to the domain and to the frequency of the time series. For instance, it can be used to predict retail or electricity demand, as well as server metrics. On European day ahead electricity prices, t0 reduces the error by a third compared with a naive baseline that repeats the previous day. Adding weather forecasts or holiday information improves it even further. There is a Colab notebook to try it. t0 has also been tested independently on electricity prices in Texas (ERCOT). https://colab.research.google.com/github/theforec