The XiYanSQL-QwenCoder-32B-2504 model by XGenerationLab is a 32 billion parameter SQL generation model with a 32768 token context length. It is specifically optimized for generating SQL queries across multiple dialects, including SQLite, PostgreSQL, and MySQL. This model incorporates fine-tuning and GRPO training strategies to achieve high efficiency and accuracy in text-to-SQL tasks, demonstrating improved generalization capabilities on out-of-domain datasets.
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Overview
The XGenerationLab/XiYanSQL-QwenCoder-32B-2504 is a 32 billion parameter model designed for advanced SQL generation. It leverages a combination of fine-tuning and GRPO (Gradient-based Policy Optimization) training without a thinking process, aiming for both efficiency and accuracy in converting natural language to SQL queries. The model supports multiple SQL dialects, including SQLite, PostgreSQL, and MySQL, and shows strong generalization capabilities across different dialects and out-of-domain datasets.
Key Capabilities
- Multi-Dialect SQL Generation: Excels at generating SQL for SQLite, PostgreSQL, and MySQL.
- Enhanced Performance: Achieves high accuracy on standard benchmarks like BIRD and Spider, and performs well on a real-world DW test set with complex queries.
- Improved Generalization: Demonstrates robust performance on out-of-domain datasets, reflecting its adaptability.
- Optimized Training: Utilizes a unique blend of fine-tuning and GRPO training for efficient and accurate SQL output.
Performance Highlights
The 32B model achieves notable results on various benchmarks:
- BIRD Dev@M-Schema: 67.14%
- Spider Test@M-Schema: 89.20%
- DW PostgreSQL@M-Schema: 53.52%
- DW MySQL@M-Schema: 57.74%
These metrics indicate strong performance compared to other models in its class, particularly on complex, real-world SQL scenarios.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.