The defog/sqlcoder-7b-2 is a 7 billion parameter large language model developed by Defog, Inc., fine-tuned from CodeLlama-7B. This model specializes in natural language to SQL generation, excelling particularly in complex SQL operations like joins. It is designed to help non-technical users understand data within SQL databases by converting natural language questions into accurate SQL queries.
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Overview
defog/sqlcoder-7b-2 is a 7 billion parameter language model developed by Defog, Inc., specifically designed for natural language to SQL generation. It is fine-tuned from CodeLlama-7B and was updated in February 2024 for improved performance, especially concerning SQL joins.
Key Capabilities
- Natural Language to SQL Conversion: Translates user questions into executable SQL queries.
- Optimized for Joins: The latest model weights significantly enhance its ability to handle SQL queries involving joins.
- Database Schema Awareness: Generates queries based on provided database schema DDL statements.
- Evaluation Framework: Evaluated using SQL-Eval, a PostgreSQL-based framework developed by Defog.
Performance Highlights
On the SQL-Eval benchmark, sqlcoder-7b-2 demonstrates strong performance across various SQL categories:
- Date: 96%
- Group By: 91.4%
- Order By: 94.3%
- Ratio: 91.4%
- Join: 94.3%
- Where: 77.1%
Intended Use Cases
This model is primarily intended as an analytics tool for non-technical users to query data in SQL databases. It is crucial to note that it is designed for use with read-only access to databases, as it has not been trained to reject malicious requests from users with write access.