This is a variant of the Chronos-2 model which has
only
been trained on synthetic univariate and multivariate data. For usage and details on the Chronos-2 model, please refer to
https://huggingface.co/autogluon/chronos-2
.
Citation
If you find Chronos-2 useful for your research, please consider citing the associated paper:
@article{ansari2025chronos2,
title = {Chronos-2: From Univariate to Universal Forecasting},
author = {Abdul Fatir Ansari and Oleksandr Shchur and Jaris Küken and Andreas Auer and Boran Han and Pedro Mercado and Syama Sundar Rangapuram and Huibin Shen and Lorenzo Stella and Xiyuan Zhang and Mononito Goswami and Shubham Kapoor and Danielle C. Maddix and Pablo Guerron and Tony Hu and Junming Yin and Nick Erickson and Prateek Mutalik Desai and Hao Wang and Huzefa Rangwala and George Karypis and Yuyang Wang and Michael Bohlke-Schneider},
year = {2025},
url = {https://arxiv.org/abs/2510.15821}
}
Runs of autogluon chronos-2-synth on huggingface.co
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More Information About chronos-2-synth huggingface.co Model
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chronos-2-synth is an open source model from GitHub that offers a free installation service, and any user can find chronos-2-synth on GitHub to install. At the same time, huggingface.co provides the effect of chronos-2-synth install, users can directly use chronos-2-synth installed effect in huggingface.co for debugging and trial. It also supports api for free installation.