Explore the convergence of OpenVINO and Optimum-Intel in this post, where I detail the setup and execution of example code on my aging laptop. Focused on applying Quantization-aware Training and the Token Merging method to optimize the UNet model within the Stable Diffusion pipeline, this journey showcases the synergy of open-source tools for deep learning model deployment. Note that the provided code is tailored for CPU-based inference due to limitations in my aging GeForce graphics card, making it a valuable resource for users with similar hardware constraints. Dive into the world of optimized models and delightful Pokemon creation!