tokaka22/s2ip-llm

Official reponsitory for "S^2IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting"

S2IP-LLM

Official reponsitory for "S^2IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting"

🛠 Prerequisites

Ensure you have installed the necessary dependencies by first building environment:

conda create -n "myenv" python=3.10.0
conda activate myenv

Inside the folder, run:

pip install -r requirements.txt

📊 Prepare Datasets

Begin by downloading the required datasets. All datasets are conveniently available at Autoformer. Create a separate folder named ./data

💻 Training

All scripts are located in ./scripts. Example:

cd Long-term_Forecasting 
sh scripts/etth1.sh

📚 Citation

If you find this repo useful, please consider citing our paper as follows:

@inproceedings{pan2024s,
  title={$ S\^{} 2$ IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting},
  author={Pan, Zijie and Jiang, Yushan and Garg, Sahil and Schneider, Anderson and Nevmyvaka, Yuriy and Song, Dongjin},
  booktitle={Forty-first International Conference on Machine Learning},
  year={2024}
}