TableGPT2 7B Model details We developed and released TableGPT2 7B, a large scale decoder specifically tailored for data intensive tasks, with a focus on interpreting and analyzing tabular data. TableGPT2 7B is designed to bridge the gap between conventional LLM capabilities and the real world demands of tabular/structured data tasks, such as those in business intelligence (BI), automated data driven analysis, and application tasks tightly involving databases or data warehouses. Model Developers Zhejiang University Variations TableGPT2 is available in two configurations—7B and 72B parameters—both derived from the Qwen2.5 model family and optimized for handling structured data in tabular formats. Currently, we have released the 7B version to the public. Input TableGPT2 7B accepts both text and tabular data as input, with the tabular data structured as text in the format of a df.head() result. Output TableGPT2 7B produces text based outputs, specifically optimized for coding tasks, data interpretation, and BI focused question answering. Language Our model places a strong emphasis on Chinese corpora, and currently, queries in other languages may have limited support. Other Requirements…
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