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This is new updated version of Moirai-1.0-R (https://huggingface.co/Salesforce/moirai-1.0-R-base).
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The Moirai-1.1-R model achieved significant improvements (~20%) for low-frequency cases like Yearly and Quarterly data in Normalised Mean Absolute Error (NMAE) for 40 datasets on the Monash repository.
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This is new updated version of Moirai-1.0-R (https://huggingface.co/Salesforce/moirai-1.0-R-base).
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The Moirai-1.1-R model achieved significant improvements (~20%) for low-frequency cases like Yearly and Quarterly data in Normalised Mean Absolute Error (NMAE) for 40 datasets on the Monash repository.
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## Ethical Considerations
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This release is for research purposes only in support of an academic paper.
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Our models, datasets, and code are not specifically designed or evaluated for all downstream purposes.
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We strongly recommend users evaluate and address potential concerns related to accuracy, safety, and fairness before deploying this model.
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We encourage users to consider the common limitations of AI, comply with applicable laws, and leverage best practices when selecting
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use cases, particularly for high-risk scenarios where errors or misuse could significantly impact people’s lives, rights, or safety.
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For further guidance on use cases, refer to our AUP and AI AUP.
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