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Large time-series model introduced in this [paper](https://arxiv.org/abs/2402.02368) and enhanced with our [further work](https://arxiv.org/abs/2410.04803).
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This version is univariate pre-trained on **260B** time points with **84M** parameters, a lightweight generative Transformer for zero-shot point forecasting.
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We evaluate the model on the following benchmark: [TSLib Dataset](https://cdn-uploads.huggingface.co/production/uploads/64fbe24a2d20ced4e91de38a/AXhZLVGR8Cnuxe8CVK4Fu.png).
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Large time-series model introduced in this [paper](https://arxiv.org/abs/2402.02368) and enhanced with our [further work](https://arxiv.org/abs/2410.04803).
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This version is univariate pre-trained on **260B** time points with **84M** parameters, a lightweight generative Transformer for zero-shot point forecasting.
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We evaluate the model on the following benchmark: [TSLib Dataset](https://cdn-uploads.huggingface.co/production/uploads/64fbe24a2d20ced4e91de38a/AXhZLVGR8Cnuxe8CVK4Fu.png).
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