#python

TimesFM is a powerful time-series forecasting model from Google Research, pretrained on 100 billion real-world data points, making it highly accurate even without retraining on new data. The latest version, TimesFM 2.5, is smaller (200M parameters) but supports longer input sequences and advanced forecasting features like continuous quantile forecasts. It can handle multiple time series and external factors, improving prediction quality for tasks like demand planning or weather forecasting. You can easily install and use it with Python, benefiting from fast, reliable forecasts across many applications without needing extensive model training. This saves time and effort while providing strong results.

https://github.com/google-research/timesfm