When working with machine learning workflows, modular sampling can provide a more intuitive and flexible approach to constructing models. In the previous article, I showed you how to set up the Flux model using a standard case sampler node. In this guide, we’ll explore how to set up a modular workflow using the SamplerCustomAdvanced node, focusing on … Read more
Introduction The SDXL model offers powerful capabilities for image generation and refinement, making it a popular choice for creative workflows. In this article, we’ll explore how to set up the full SDXL workflow using both the base model and the refiner model. By leveraging these models effectively, you can produce high-quality images with improved details and artistic … Read more
When working with AI-powered image generation tools like ComfyUI, understanding inference steps and CFG (classifier-free guidance) scale is essential for producing high-quality results. In this article, we’ll explore how these parameters affect image generation and how to adjust them to achieve the best outcomes. Understanding Inference Steps Inference steps, also known as sampling steps, define … Read more
When working with diffusion models, understanding the mechanics of samplers and schedulers is crucial to achieving optimal results. These components influence how noise is removed from the latent space, shaping the quality and characteristics of the final output. This guide delves deeper into how samplers work, explains their importance, and provides actionable steps to select … Read more