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README.md
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[](https://huggingface.co/Melady/TEMPO)
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[](https://opensource.org/licenses/Apache-2.0)
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The official model card for ICLR 2024 paper: "TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting (ICLR 2024)".
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TEMPO is one of the very first open source **Time Series Foundation Models** for forecasting task v1.0 version.
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## 💡 Demos
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bash [ecl, etth1, etth2, ettm1, ettm2, traffic, weather]_test.sh
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```
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## Pre-trained Models
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Here is the prompts use to generate the coresponding textual informaton of time series via [[OPENAI ChatGPT-3.5 API]](https://platform.openai.com/docs/guides/text-generation)
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The time series data are come from [[S&P 500]](https://www.spglobal.com/spdji/en/indices/equity/sp-500/#overview). Here is the EBITDA case for one company from the dataset:
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Example of generated contextual information for the Company marked above:
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[](https://huggingface.co/Melady/TEMPO)
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[](https://opensource.org/licenses/Apache-2.0)
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The official model card for ICLR 2024 paper: "TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting (ICLR 2024)".
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TEMPO is one of the very first open source **Time Series Foundation Models** for forecasting task v1.0 version.
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## 💡 Demos
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bash [ecl, etth1, etth2, ettm1, ettm2, traffic, weather]_test.sh
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```
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## Pre-trained Models
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Here is the prompts use to generate the coresponding textual informaton of time series via [[OPENAI ChatGPT-3.5 API]](https://platform.openai.com/docs/guides/text-generation)
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The time series data are come from [[S&P 500]](https://www.spglobal.com/spdji/en/indices/equity/sp-500/#overview). Here is the EBITDA case for one company from the dataset:
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Example of generated contextual information for the Company marked above:
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