TinyTimeMixers (TTMs) are compact pre-trained models for multivariate time-series forecasting, open-sourced by IBM Research. With less than 1 million parameters, TTM introduces the first-ever “tiny” pre-trained models for time-series forecasting. TTM outperforms several popular benchmarks demanding billions of parameters in zero-shot and few-shot forecasting and can easily be fine-tuned for multi-variate forecasts. This notebook demonstrates how to apply Granite Time Series TTMs to forecast energy demand. You will need a Hugging Face token to run this recipe in Colab. Instructions for obtaining this credential can be found here.Documentation Index
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