This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on the generator dataset. It achieves the following results on the evaluation set:

This repository contains a fine-tuned version of the Mistral 7B model, tailored specifically for text-to-SQL tasks. The model is designed to convert natural language queries into structured SQL queries, enabling seamless interaction with databases through conversational language.

The Mistral-7B-Text2SQL model is intended for applications that require converting natural language queries into SQL commands. Suitable use cases include:

Conversational Agents: Allowing users to retrieve information from databases through natural language interaction. Data Analytics: Enabling non-technical users to query databases without needing to know SQL syntax. Business Intelligence: Supporting decision-making processes by simplifying data access.

The model was fine-tuned using the generator dataset, which consists of a variety of natural language queries paired with corresponding SQL commands. The dataset is designed to cover a wide range of query types, allowing the model to generalize better across different types of SQL queries.

Dataset Characteristics Diversity: The dataset includes examples from various domains, ensuring that the model learns to handle a broad spectrum of queries. Size: (Include the size of the dataset, e.g., the number of examples if available.) Annotations: Each example includes natural language input along with the expected SQL output, facilitating supervised learning.