This paper introduces and explores a new programming paradigm, Model-based Programming, designed to address the challenges inherent in applying deep learning models to real-world applications. Despite recent significant successes of deep learning models across a range of tasks, their deployment in real business scenarios remains fraught with difficulties, such as complex model training, large computational resource requirements, and integration issues with existing programming languages. To ameliorate these challenges, we propose the concept of 'Model-based Programming' and present a novel programming language - M Language, tailored to a prospective model-centered programming paradigm. M Language treats models as basic computational units, enabling developers to concentrate more on crucial tasks such as model loading, fine-tuning, evaluation, and deployment, thereby enhancing the efficiency of creating deep learning applications. We posit that this innovative programming paradigm will stimulate the extensive application and advancement of deep learning technology and provide a robust foundation for a model-driven future.

翻译：本文介绍并探索了一种新的编程范式——基于模型的编程，旨在应对深度学习模型在实际应用中所面临的挑战。尽管近年来深度学习模型在各类任务中取得了显著成功，但其在真实业务场景中的部署仍困难重重，例如模型训练复杂、计算资源需求庞大、以及与现有编程语言的集成问题。为缓解这些挑战，我们提出了“基于模型的编程”概念，并设计了一门新型编程语言——M语言，以适配以模型为中心的编程范式。M语言将模型视为基本计算单元，使开发者能够更专注于模型加载、微调、评估与部署等关键任务，从而提升深度学习应用的开发效率。我们相信，这一创新编程范式将推动深度学习技术的广泛应用与进步，并为以模型驱动的未来奠定坚实基础。