🌟 EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuning

🚀 Installation

cd EffiCoder
pip install -r requirements.txt
cd LLaMA-Factory
pip install -e ".[torch,metrics]"

🔧 Fine-tune LLMs with EffiCoder

We have provided the EffiCoder dataset in EffiCoder/LLaMA-Factory/data/efficoder.json, so we can directly use SFT and other methods to finetune LLMs.

Replace {your_directory_path} with the absolute path to the directory where you have placed EffiCoder/datasets/efficoder.json in EffiCoder/LLaMA-Factory/data/dataset_info.json.

cd EffiCoder/LLaMA-Factory
bash run.sh

⚡ VLLM Inference

cd EffiCoder/scripts
bash run.sh

📊 Report Efficiency and pass@1 Results

cd EffiCoder/src
python code_efficiency_calculator.py
python calculate_memory_usage.py

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Happy tuning! 🎉 Feel free to open an issue if you encounter any problems. 🛠️