Natural Language to SQL Query using an Open Source LLM

Introduction

In the dynamic landscape of data utilization, the ability to
effortlessly interact with databases is paramount. Traditionally, this
interaction required a deep understanding of Structured Query Language
(SQL), posing a barrier to entry for many users. However, the advent of
Natural Language Processing (NLP) to SQL Query Engines has transformed
this landscape, allowing users to communicate with databases
using natural language commands. This cutting-edge technology seamlessly translates human language into SQL queries, revolutionizing how we retrieve and manipulate data.

In Natural Language Processing (NLP), models like
Mistral 7B and Microsoft Phi-3 are at the forefront, redefining the
boundaries of performance and efficiency.

Mistral 7B stands out for its remarkable performance and precision in
NLP tasks. With innovative features like Grouped-Query Attention (GQA)
and Sliding Window Attention (SWA), Mistral 7B excels in various
benchmarks, including mathematics and code generation. Its ability to
approach the coding proficiency of Code-Llama 7B while maintaining
excellence across diverse domains underscores its significance in NLP
advancement.