Code language models require repository-specific context to accurately resolve imports, APIs, and project conventions. However, existing methods for injecting this knowledge, such as per-repository fine-tuning and LoRA, are costly and brittle, particularly in the face of evolving codebases. Code2LoRA, a novel hypernetwork framework, addresses this limitation by generating repository-specific adapters for code language models, enabling more efficient and adaptable processing of software evolution1. This approach has significant implications for the development and maintenance of large-scale software projects, where the ability to rapidly adapt to changing codebases is crucial. By reducing the computational overhead and improving the robustness of code language models, Code2LoRA has the potential to enhance the overall security and reliability of software systems, making it a critical consideration for practitioners and developers seeking to mitigate the risks associated with software evolution.