Optimizing Large Language Models to Expedite the Development of Smart Contracts

TL;DR

This paper presents MazzumaGPT, a large language model optimized for generating smart contract code to help developers build web3 applications more efficiently, addressing skill gaps and improving productivity.

Contribution

The paper introduces MazzumaGPT, a specialized LLM for smart contract development, detailing its optimization, fine-tuning, and performance evaluation.

Findings

MazzumaGPT effectively generates functionally correct smart contracts.

Optimization improves model accuracy and developer productivity.

The model's limitations and broader impacts are discussed.

Abstract

Programming has always been at the heart of technological innovation in the 21st century. With the advent of blockchain technologies and the proliferation of web3 paradigms of decentralised applications, smart contracts have been very instrumental in enabling developers to build applications that reside on decentralised blockchains. Despite the huge interest and potential of smart contracts, there is still a significant knowledge and skill gap that developers need to cross in order to build web3 applications. In light of this, we introduce MazzumaGPT, a large language model that has been optimised to generate smart contract code and aid developers to scaffold development and improve productivity. As part of this research, we outline the optimisation and fine-tuning parameters, evaluate the model's performance on functional correctness and address the limitations and broader impacts of our research.