Instructions to use SequentialLearning/DualTime-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SequentialLearning/DualTime-8B with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
added arxiv link
Browse files
README.md
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# DualTime-8B
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<p align="center">
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<a href="
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<a href="https://github.com/azencot-group/dual-time"><img src="https://img.shields.io/badge/GitHub-Code-181717?logo=github" alt="Code"/></a>
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<a href="https://huggingface.co/datasets/SequentialLearning/DualTime-data"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Data-yellow" alt="Data"/></a>
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</p>
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TSExam 0.899, TSRBench 53.2, ChatTS alignment A 0.864 / 0.805 and B
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0.893 / 0.868 (categorical / numerical). The full tables are in the paper and
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the code repository.
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# DualTime-8B
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<p align="center">
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<a href="https://arxiv.org/abs/2610.22327"><img src="https://img.shields.io/badge/arXiv-2610.22327-b31b1b.svg" alt="arXiv"/></a>
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<a href="https://github.com/azencot-group/dual-time"><img src="https://img.shields.io/badge/GitHub-Code-181717?logo=github" alt="Code"/></a>
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<a href="https://huggingface.co/datasets/SequentialLearning/DualTime-data"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Data-yellow" alt="Data"/></a>
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</p>
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TSExam 0.899, TSRBench 53.2, ChatTS alignment A 0.864 / 0.805 and B
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0.893 / 0.868 (categorical / numerical). The full tables are in the paper and
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the code repository.
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## Citation
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```bibtex
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@misc{zisling2026twicetime,
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title={Twice Upon a Time: Complementary Representations for Time-Series Reasoning},
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author={Hedi Zisling and Liran Nochumsohn and Ilan Naiman and Mihir Parmar and Omri Azencot},
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year={2026},
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eprint={2610.22327},
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archivePrefix={arXiv},
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primaryClass={cs.LG},
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url={https://arxiv.org/abs/2610.22327},
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}
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```
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