Heather contributed to the THUDM/slime repository by addressing a stability issue in the Qwen3.5 and Qwen3_next models. She focused on improving model parameter dtype handling, replacing torch.get_current_dtype() with torch.get_default_dtype() to ensure consistent data types during inference. This targeted fix, implemented in Python using PyTorch, mitigated potential mixed-precision errors and improved reproducibility across different environments. Heather’s work resulted in a low-risk, well-scoped patch that enhanced deployment reliability for the Qwen model family. The depth of her contribution lay in identifying a subtle source of instability and delivering a precise, maintainable solution within a deep learning context.