This project aims at detecting machine-learning-specific software refactorings from machine learning projects using state-of-the-art large language models. We plan to use Llama 2 and Code Llama to obtain information from code commits and identify refactoring categories. To achieve this text classification task, the input data we will use should be the refactoring information and relevant commits. After our fine-tuning process for the large language models, the output should be the categories of the refactorings, which are either general refactorings or ML-specific refactorings. We will use the GPU resources to run and fine-tune the large language models. The demands of GPU should depend on the model size and data size. We expect to use multiple GPUs to accelerate this process.