Sql fixit - automated generation of fine-tuning data using llms

One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause:

• generating, by a large language model, from a natural language request, an incorrect database statement that, based on a first database schema, could not satisfy a technical requirement;
• generating, based on the natural language request, a correct database statement that, based on a second database schema, could satisfy the technical requirement;
• inferring, for the second database schema, a restatement of the natural language request;
• and
• supervised finetuning the large language model by:
• a) accepting, in an input to the large language model, the restatement of the natural language request,
• b) inferentially generating, by the large language model in response to said accepting, a new database statement, and
• c) backpropagating a nonzero error through the large language model in response to the new database statement being different from said correct database statement.