# Rethinking Graph Structure Learning in the Era of LLMs

Hardware environment: Intel(R) Xeon(R) Gold 6240 CPU @ 2.60GHz, NVIDIA A100 with 80GB memory.

Software environment: Ubuntu 22.04.5, Python 3.8, PyTorch 2.1.0 and CUDA 11.8.

1. Please refer to [PyTorch](https://pytorch.org/get-started/locally/) and [PyG](https://pytorch-geometric.readthedocs.io/en/latest/notes/installation.html) to install the environments;
2. Run 'pip install -r requirements.txt' to download required packages;

Running

To run the model in this paper

1. Place the dataset in the "datasets" folder, following the format of the Cora dataset we provided as a reference.
2. Download the GLM-4-9b-chat model (it can be downloaded via ModelScope).
3. Open main.py to run LLaTA.
    
    Run this command:
    
    ```python
    python main.py --gnn_type gcn --data_name cora --llm_path your llm path
    ```