I will create a tag table augmented generation model

Table Augmented Generation (TAG) refers to a method that enhances text generation models by incorporating structured data from tables.

  - The model receives both unstructured text data (like prompts or questions) and structured data in tabular form. Tables may contain various types of information, such as numerical data, categorical values, or relationships.

  - The system retrieves relevant data from the tables based on the input query. This can involve querying a database or filtering a dataset to find the most pertinent rows or columns.

  - The model analyzes both the unstructured text and the structured table data to understand the context. It identifies how the table data can support or enhance the text generation process.

  - The model integrates the retrieved table data into the text generation process. This can involve using the table data to provide factual support, fill in gaps in information, or generate answers based on the structured data.

  - Using the combined context of the prompt and the table data, the model generates coherent and contextually relevant text. This could involve summarizing data, explaining re