Yangjun focused on expanding the capabilities of the embeddings-benchmark/mteb repository by integrating the infly/inf-retriever-v1 model into its benchmarking suite. Using Python, he managed both metadata management and model integration, creating a dedicated inf_models.py file to register the new model and updating overview.py to ensure seamless recognition and evaluation within the benchmark. This work laid the foundation for broader model support, allowing users to assess the latest retriever models for production use. Over the course of the month, Yangjun concentrated on feature delivery rather than bug fixes, demonstrating depth in model integration and careful attention to metadata structure.