用微调LLM自动生成代码文档，免去昂贵API费用
Free and Customizable Code Documentation with LLMs: A Fine-Tuning Approach
- 基于微调LLM生成代码文档，支持自定义仓库
- 开源工具可本地运行，避免依赖昂贵API
- 提供微调功能和数据准备指南，适合开发者自研
自动化生成编程源码文档是一项具有重要实际与科学意义的挑战性任务。我们提出一个基于大语言模型（LLM）的应用，供开发者作为辅助工具，为任何公开可访问的代码仓库生成基础文档。过去十年中，已有大量研究尝试使用神经网络架构生成代码文档。随着大语言模型技术的进步，一些开源应用也相继出现。然而，这些应用通常依赖OpenAI API，对大型仓库会产生显著的财务成本。此外，目前尚无开源项目提供可微调的模型或支持用户自行微调的功能。同时，找到合适的微调数据也常面临困难。我们的应用解决了上述问题，现已发布于 https://pypi.org/project/readme-ready/。
原文摘要 · Abstract (English)
Automated documentation of programming source code is a challenging task with significant practical and scientific implications for the developer community. We present a large language model (LLM)-based application that developers can use as a support tool to generate basic documentation for any publicly available repository. Over the last decade, several papers have been written on generating documentation for source code using neural network architectures. With the recent advancements in LLM technology, some open-source applications have been developed to address this problem. However, these applications typically rely on the OpenAI APIs, which incur substantial financial costs, particularly for large repositories. Moreover, none of these open-source applications offer a fine-tuned model or features to enable users to fine-tune. Additionally, finding suitable data for fine-tuning is often challenging. Our application addresses these issues which is available at https://pypi.org/project/readme-ready/.
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