# ChatTS-14B Model
`ChatTS` focuses on **Understanding and Reasoning** about time series, much like what vision/video/audio-MLLMs do.
This repo provides code, datasets and model for `ChatTS`: [ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and Reasoning](https://arxiv.org/pdf/2412.03104).

Here is an example of a ChatTS application, which allows users to interact with a LLM to understand and reason about time series data:
![Chat](figures/chat_example.png)

## Usage
This model is fine-tuned on the QWen2.5-14B-Instruct (https://huggingface.co/Qwen/Qwen2.5-14B-Instruct) model. For more usage details, please refer to the `README.md` in the ChatTS repository.

## Reference
- QWen2.5-14B-Instruct (https://huggingface.co/Qwen/Qwen2.5-14B-Instruct)
- transformers (https://github.com/huggingface/transformers.git)
- [ChatTS Paper](https://arxiv.org/pdf/2412.03104)

## License
This model is licensed under the [Apache License 2.0](LICENSE).

## Cite
```
@article{xie2024chatts,
  title={ChatTS: Aligning Time Series with LLMs via Synthetic Data for Enhanced Understanding and Reasoning},
  author={Xie, Zhe and Li, Zeyan and He, Xiao and Xu, Longlong and Wen, Xidao and Zhang, Tieying and Chen, Jianjun and Shi, Rui and Pei, Dan},
  journal={arXiv preprint arXiv:2412.03104},
  year={2024}
}
```