defog/sqlcoder-34b-alpha
Defog's SQLCoder-34B-Alpha is a 34 billion parameter language model fine-tuned on a CodeLlama base, specifically designed for converting natural language questions into SQL queries. It significantly outperforms GPT-4 and other popular open-source models on novel SQL generation datasets, demonstrating high accuracy across various query categories. The model is optimized for SQL generation tasks, making it a powerful tool for database interaction and data analysis.
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Defog SQLCoder-34B-Alpha: Natural Language to SQL Generation
Defog's SQLCoder-34B-Alpha is a 34 billion parameter model built upon a CodeLlama base, engineered to excel at transforming natural language questions into precise SQL queries. This model has been rigorously fine-tuned on over 20,000 human-curated questions across 10 distinct schemas, ensuring robust performance on diverse and novel datasets not seen during training.
Key Capabilities & Performance
- Superior SQL Generation: SQLCoder-34B-Alpha achieves an 84.0% correctness rate on the
sql-evalframework, surpassinggpt-4andgpt-4-turbo(both at 82.5%) on novel datasets. - Category-Specific Accuracy: Demonstrates strong performance across various SQL query categories, including
group_by(94.3%),order_by(88.6%), andjoin(82.9%). - Open-Source & Commercial Use: The model weights are licensed under CC BY-SA 4.0, permitting commercial use and modification, provided modified weights are open-sourced under the same terms.
Use Cases & Hardware
- Efficient Database Interaction: Ideal for applications requiring accurate and efficient conversion of user queries into SQL, streamlining data access and analysis.
- Accessible Deployment: Can be run on consumer GPUs with 20GB+ memory (e.g., RTX 4090, RTX 3090, Apple M2 Pro/Max/Ultra) using 8-bit or 4-bit quantization, or on 4xA10 GPUs with
float16weights.