| # iLoRA | |
| #### Preparation | |
| 1. Prepare the environment: | |
| ```python | |
| git clone | |
| cd iLoRA | |
| pip install -r requirements.txt | |
| ``` | |
| 2. Prepare the pre-trained huggingface model of Llama2-7B (https://huggingface.co/meta-llama/Llama-2-7b-hf). | |
| 3. Modify the paths inside the .sh file. | |
| #### Train iLoRA | |
| Train iLoRA with a single A100 GPU on MovieLens dataset: | |
| ```python | |
| sh train_movielens.sh | |
| ``` | |
| Train iLoRA with a single A100 GPU on Steam dataset: | |
| ``` | |
| sh train_steam.sh | |
| ``` | |
| Train iLoRA with a single A100 GPU on LastFM dataset: | |
| ``` | |
| sh train_lastfm.sh | |
| ``` | |
| Note that: set the `llm_path` argument with your own directory path of the Llama2 model. | |
| ##### For the environmental issues mentioned by everyone during the reproduction process, we have attempted to help resolve them and have listed some solutions: | |
| If you encounter an error with your transformers/generation/utils.py file, please replace it with the debug/utils.py file we have provided in your environment. | |
| If you encounter an error with your transformers/models/llama/modeling_llama.py file, please replace it with the debug/modeling_llama.py file. | |
| Thank you all for your attention to our work! Wishing you success in your research. | |
| ##### Evaluate iLoRA | |
| Test iLoRA with a single A100 GPU on MovieLens dataset: | |
| ``` | |
| sh test_movielens.sh | |
| ``` | |
| Test iLoRA with a single A100 GPU on Steam dataset: | |
| ``` | |
| sh test_steam.sh | |
| ``` | |
| Test iLoRA with a single A100 GPU on LastFM dataset: | |
| ``` | |
| sh test_lastfm.sh | |
| ``` | |