May 2025 performance summary for two repositories: ModelCloud/GPTQModel and liguodongiot/transformers. Key features delivered include Qwen-Omni Multimodal Support for ModelCloud/GPTQModel, enabling processing of text and audio inputs, with unit tests and updated requirements. Major bug fix delivered: robust loading of quantized weights for Qwen2.5-Omni and proper LayerNorm initialization in liguodongiot/transformers, with updates to modeling_qwen2_5_omni.py to ensure consistency. Impact: expanded multimodal capabilities and improved reliability of quantized-weight handling, plus enhanced test coverage and CI robustness. This work adds business value by enabling broader use cases, reducing deployment risk, and improving maintainability. Technologies/skills demonstrated include Python, ML model deployment, test-driven development, quantization (AutoAWQ), LayerNorm handling, and cross-repo collaboration.