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README.md
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We present GIFT-Eval, a benchmark designed to advance zero-shot time series forecasting by facilitating evaluation across diverse datasets. GIFT-Eval includes 23 datasets covering 144,000 time series and 177 million data points, with data spanning seven domains, 10 frequencies, and a range of forecast lengths. This benchmark aims to set a new standard, guiding future innovations in time series foundation models.
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[📄 Paper](https://arxiv.org/abs/2410.10393)
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[🖥️ Code](https://github.com/SalesforceAIResearch/gift-eval)
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We present GIFT-Eval, a benchmark designed to advance zero-shot time series forecasting by facilitating evaluation across diverse datasets. GIFT-Eval includes 23 datasets covering 144,000 time series and 177 million data points, with data spanning seven domains, 10 frequencies, and a range of forecast lengths. This benchmark aims to set a new standard, guiding future innovations in time series foundation models.
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To facilitate the effective pretraining and evaluation of foundation models, we also provide a non-leaking pretraining dataset --> [GiftEvalPretrain](https://huggingface.co/datasets/Salesforce/GiftEvalPretrain).
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[📄 Paper](https://arxiv.org/abs/2410.10393)
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[🖥️ Code](https://github.com/SalesforceAIResearch/gift-eval)
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