Llama 2 represents a significant advancement in open-source large language models (LLMs), rivaling the performance of GPT-3.5 in many benchmarks and offering a promising option for complex applications. However, the smallest model variant, Llama-2–7B, struggles with generating SQL statements, making it less suitable for structured analytics without further fine-tuning. This process involves adjusting the model's parameters using a text-to-SQL dataset, as shown in a tutorial that simplifies the finetuning process. The tutorial uses tools like Modal for orchestration and LlamaIndex for text-to-SQL inference, demonstrating a marked improvement in the model's SQL generation capabilities post-finetuning. The tutorial is designed to be accessible, offering a step-by-step guide to integrating a finetuned Llama 2 model into text-to-SQL workflows, thereby enhancing its utility in database querying tasks.