This is the Windows app named TimesFM whose latest release can be downloaded as TimesFM-2.0.2sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS:
TimesFM
DESCRIPTION:
TimesFM is a pretrained time-series foundation model from Google Research built for forecasting tasks, designed to generalize across many domains without requiring extensive per-dataset retraining. It provides a decoder-only model approach to forecasting, aiming for strong performance even in zero-shot or low-data settings where traditional models often struggle. The project includes code and an inference API intended to make it practical to run forecasts programmatically, with options to use different backends such as Torch or Flax depending on your environment and performance needs. Newer releases emphasize expanded context handling and more flexible forecasting outputs, including quantile forecasting so users can get uncertainty estimates rather than only point predictions. The repository also documents how model versions evolved, with newer variants focusing on efficiency and longer context windows while maintaining forecasting quality.
Features
- Pretrained foundation model for time-series forecasting
- Supports long context windows in newer model versions
- Point forecasts plus quantile forecasts for uncertainty estimation
- Multiple inference backends such as Torch and Flax
- Versioned checkpoints with an upgrade path across releases
- Optional covariate support via XReg in newer releases
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/timesfm.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.