This study introduces a novel approach to enhance e-commerce chatbots using the Falcon-7B model, a state-of-the-art Large Language Model (LLM) with 7 billion parameters. Trained on a vast dataset of 1,500 billion tokens, the Falcon-7B model excels in natural language understanding and generation. The model's 16-bit full quantization transformer ensures efficient computation without compromising scalability or performance. The study aims to redefine e-commerce chatbot systems by providing businesses with a robust solution for delivering personalized customer experiences. The Falcon-7B model demonstrates superior performance in natural language tasks, outperforming other models like GPT2, GP2-XL, and DistilGPT2 in the Ecommerce-FAQ-Chatbot-Dataset task. The research highlights the potential of LLMs in advancing e-commerce chatbot technology and improving customer service.This study introduces a novel approach to enhance e-commerce chatbots using the Falcon-7B model, a state-of-the-art Large Language Model (LLM) with 7 billion parameters. Trained on a vast dataset of 1,500 billion tokens, the Falcon-7B model excels in natural language understanding and generation. The model's 16-bit full quantization transformer ensures efficient computation without compromising scalability or performance. The study aims to redefine e-commerce chatbot systems by providing businesses with a robust solution for delivering personalized customer experiences. The Falcon-7B model demonstrates superior performance in natural language tasks, outperforming other models like GPT2, GP2-XL, and DistilGPT2 in the Ecommerce-FAQ-Chatbot-Dataset task. The research highlights the potential of LLMs in advancing e-commerce chatbot technology and improving customer service.