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TimesFM is a basic decoder model pre-trained on a large time series data set with 20 billion parameters. Although smaller in scale than large language models, its zero-shot performance is close to state-of-the-art supervised methods on multiple unseen datasets in different domains and time granularities. TimesFM provides excellent unseen time series predictions without additional training.
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