Lucia Rose Quirke developed a cross-repository Steered Transformer capability for the red-hat-data-services/lm-evaluation-harness and swiss-ai/lm-evaluation-harness projects. She introduced a new 'steered' model type that enables fine-grained control over Hugging Face Transformer models by loading steering configurations from PyTorch files or CSVs. This approach allows for rapid experimentation and supports business-aligned model personalization in NLP evaluation workflows. Lucia implemented the feature using Python and PyTorch, updating documentation and expanding test coverage to ensure reliability. Her work established consistent model steering infrastructure across both repositories, laying the groundwork for faster iteration and broader applicability in machine learning evaluation tasks.