Improving Stable Diffusion Images with FreeU - Optimizing SDXL, LCM, and Turbo Models

Overview

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Dive into an in-depth 58-minute tutorial on optimizing Stable Diffusion images using FreeU hyperparameters. Explore the ComfyRoll custom nodes and ComfyUI API to conduct grid searches for ideal b1, b2, s1, and s2 parameters. Learn to fine-tune SDXL, integrate LCM LoRA, and work with SDXL Turbo. Follow along as the process of debugging grid errors, analyzing dynamic values, and comparing results is demonstrated. Gain insights into handling asynchronous API calls, extracting LoRAs, and setting up efficient workflows. By the end, acquire the skills to significantly enhance image quality across various Stable Diffusion models and configurations.

Syllabus

Introduction
FreeU paper
How do b and s value interact
ComfyRoll nodes
CivitAI workflows downloads
ComfyRoll workflows
ComfyRoll Grid error
Debugging the grid error
Trying out ComfyRoll XY list
Finding a fix for grid error
ComfyUI API
ComfyUI API JSON
How to request ComfyUI API
Re-evaluating the API JSON file
Code overview
Selecting baseline freeU s values
Handling asynchronous calls as ComfyUI API doesn't have callbacks
Setting up code environment
Executing the code
Analyzing the dynamic b values for normal FreeU
Narrowing the search window
Why choose static s values of 1.1 and 0.2? Why not use 0, 0 or 1, 1?
Dynamic s values
Getting original seed value
Pointing out my mistake with my seed value wasn't working
Comparing with original generations as a sanity check
Comparing results so far
Workflow for kohya deep shrink
LCM workflow
Dynamic b values for LCM
Dynamic s values for LCM
Updated comparison of all results so far
Extracting SDXL turbo LoRA
SDXL Turbo LoRA workflow
Dynamic b values for SDXL Turbo
Comparing different b1, b2 values for SDXL Turbo
Dynamic s values for SDXL Turbo
Final comparison of all results so far

Taught by

kasukanra

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