zenlm/zen-sql
zenlm/zen-sql is an 8 billion parameter Qwen3-based language model developed by Hanzo AI, Zoo Labs Foundation, and Lux Partners Limited, specifically fine-tuned for SQL-related tasks. It excels at complex query generation, schema design, query optimization, and database documentation across various SQL dialects including PostgreSQL, MySQL, SQLite, BigQuery, and Snowflake. This model leverages identity training, agentic-data fine-tuning, and abliteration to specialize in SQL applications.
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Overview
zenlm/zen-sql is an 8 billion parameter language model built upon the Qwen3 architecture, developed through a collaboration between Hanzo AI, Zoo Labs Foundation, and Lux Partners Limited. It features a 32K context window and is released under the Apache 2.0 license, allowing for commercial use, local deployment, and further fine-tuning. The model is specifically fine-tuned from Qwen/Qwen3-8B with additional identity training, agentic-data fine-tuning, and abliteration techniques by Hanzo.
Key Capabilities
- SQL Specialization: Designed as a dedicated SQL expert.
- Complex Query Generation: Capable of generating intricate SQL queries.
- Schema Design: Assists in the creation and structuring of database schemas.
- Query Optimization: Provides support for optimizing existing SQL queries.
- Database Documentation: Aids in generating documentation for database structures and operations.
- Multi-Dialect Support: Supports a wide range of SQL dialects including PostgreSQL, MySQL, SQLite, BigQuery, and Snowflake.
Good For
- Developers and data professionals needing assistance with SQL query development.
- Automating aspects of database management and documentation.
- Integrating SQL generation and optimization into applications.
- Educational purposes for understanding and generating SQL.