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.

本文介绍和探索了一种面向模型的新编程范式-基于模型的编程，提出并介绍了一种新颖的编程语言-M Language，旨在解决将深度学习模型应用于实际业务场景中所面临的困难，通过将模型作为基本的计算单元，使开发者更专注于重要任务，如模型加载、微调、评估和部署，从而提高创造深度学习应用程序的效率，并为以模型为中心的未来提供一个强大的基础。

基于模型的编程：为深度学习时代重新定义编程的原子单位