TableGPT2-7B is a large-scale decoder model developed by Zhejiang University, specifically designed for data-intensive tasks, particularly the interpretation and analysis of tabular data. Based on the Qwen2.5 architecture, it is optimized through Continuous Pretraining (CPT) and Supervised Fine-tuning (SFT) to handle complex table queries and business intelligence (BI) applications. It supports Chinese queries and is suitable for enterprises and research institutions that need to efficiently process structured data. The model is currently open-source and free; more professional versions may be released in the future.