Defog’s SQLCoder is a state-of-the-art LLM for converting natural language questions to SQL queries.

SQLCoder-34B is a 34B parameter model that outperforms gpt-4 and gpt-4-turbo for natural language to SQL generation tasks on our sql-eval framework, and significantly outperforms all popular open-source models.

https://huggingface.co/defog/sqlcoder-34b-alpha

SQLCoder-34B is fine-tuned on a base CodeLlama model.

Results on novel datasets not seen in training

model perc_correct

defog-sqlcoder-34b 84.0%

gpt4-turbo-2023-11-09 82.5%

gpt4-2023-11-09 82.5%

defog-sqlcoder2 77.5%

gpt4-2023-08-28 74.0%

defog-sqlcoder-7b 71.0%

gpt-3.5-2023-10-04 66.0%

claude-2 64.5%

gpt-3.5-2023-08-28 61.0%

claude_instant_1 61.0%

text-davinci-003 52.5%

Defog was trained on more than 20,000 human-curated questions. These questions were based on 10 different schemas. None of the schemas in the training data were included in our evaluation framework.

You can read more about our training approach and evaluation framework.

SQLCoder-34B has been tested on a 4xA10 GPU with float16 weights. You can also load an 8-bit and 4-bit quantized version of the model on consumer GPUs with 20GB or more of memory – like RTX 4090, RTX 3090, and Apple M2 Pro, M2 Max, or M2 Ultra Chips with 20GB or more of memory.