- Python >= 3.6
- PyTorch >= 2.1.0
- CUDA >= 11.8
| Dataset version | Description |
|---|---|
| csv | csv files include node and edge informations, including raw-texts and 128-dimention embedding Download paper, author, journal, keywords, label and move them to datasets/csv/nodeDownload paper-paper, paper-author, paper-journal, paper-keywords and move them to datasets/csv/edge |
| pt | chemistry.pt and my_graph_data.pt provides all information of node and edges. Download the datasets and move them to datasets/pt/ |
| json | json file include manufactured for GraphGPT, which includs two training stages and one eval stage. Download stage1, stage2 and eval and move them to dataset/json/ |
cd models/gnn/
conda create --name gnn python==3.10
conda activate gnn
pip install -r requirements.txt
chomd +x run.sh
./run.sh
cd models/HGN/
conda create --name hgn python==3.8
conda activate hgn
pip install -r requirements.txt
pip install dgl -f https://data.dgl.ai/wheels/repo.html
pip install openhgnn
python main.py -m model name -t node_classification -d my_custom_node_classification -g 0 --use_best_config
model names: RGCN SimpleHGN HGT NARS CompGCN HPN
cd models/LLMs
conda create --name LLM python==3.10
conda activate LLM
pip install -r requirements.txt
python chat.py
python llama_preds.py
cd models/TAPE+LLaMA
conda create --name TAPE python==3.10
conda activate TAPE
pip install -r requirements.txt
chomd +x run.sh
./run.sh
cd models/GraphGPT
conda create --name GraphGPT python==3.10
conda activate GraphGPT
pip install -r requirements.txt
chmod +x stage1.sh
./stage1.sh
chmod +x extract.sh
./extract.sh
xchmod +x stage2.sh
./stage2.sh
chmod +x eval.sh
./eval.sh
cd models/LLaGA
conda create --name llaga python==3.10
conda activate llaga
pip install -r requirements.txt
pip install flash-attn --no-build-isolation
pip install torch_geometric
pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.1.0+cu118.html
CUDA_VISIBLE_DEVICES=0 ./scripts/train.sh vicuna nc chemistry 16 chemistry
python eval/eval_pretrain.py \
--model_path /path/to/projector \
--model_base lmsys/vicuna-7b-v1.5-16k \
--conv_mode v1 \
--dataset chemistry \
--pretrained_embedding_type chemistry \
--use_hop 2 \
--sample_neighbor_size 10 \
--answers_file ./results/chemistry_nc.jsonl \
--task nc \
--cache_dir ../../checkpoint \
--template ND
python eval/eval_res.py --dataset chemistry --task nc --res_path ./results/chemistry_nc.jsonl