Granite TimeSeries TTM R1 Model Card TinyTimeMixers (TTMs) are compact pre trained models for Multivariate Time Series Forecasting, open sourced by IBM Research. With less than 1 Million parameters, TTM (accepted in NeurIPS 24) introduces the notion of 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. TTMs are lightweight forecasters, pre trained on publicly available time series data with various augmentations. TTM provides state of the art zero shot forecasts and can easily be fine tuned for multi variate forecasts with just 5% of the training data to be competitive. Refer to our paper for more details. The current open source version supports point forecasting use cases specifically ranging from minutely to hourly resolutions (Ex. 10 min, 15 min, 1 hour.). Note that zeroshot, fine tuning and inference tasks using TTM can easily be executed in 1 GPU machine or in laptops too!! New updates: TTM R1 comprises TTM variants pre trained on 250M public training samples. We have another set of TTM models released recently under TTM R2 trained on a much la…
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