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1
Introduction
2
FreeU paper
3
How do b and s value interact
4
ComfyRoll nodes
5
CivitAI workflows downloads
6
ComfyRoll workflows
7
ComfyRoll Grid error
8
Debugging the grid error
9
Trying out ComfyRoll XY list
10
Finding a fix for grid error
11
ComfyUI API
12
ComfyUI API JSON
13
How to request ComfyUI API
14
Re-evaluating the API JSON file
15
Code overview
16
Selecting baseline freeU s values
17
Handling asynchronous calls as ComfyUI API doesn't have callbacks
18
Setting up code environment
19
Executing the code
20
Analyzing the dynamic b values for normal FreeU
21
Narrowing the search window
22
Why choose static s values of 1.1 and 0.2? Why not use 0, 0 or 1, 1?
23
Dynamic s values
24
Getting original seed value
25
Pointing out my mistake with my seed value wasn't working
26
Comparing with original generations as a sanity check
27
Comparing results so far
28
Workflow for kohya deep shrink
29
LCM workflow
30
Dynamic b values for LCM
31
Dynamic s values for LCM
32
Updated comparison of all results so far
33
Extracting SDXL turbo LoRA
34
SDXL Turbo LoRA workflow
35
Dynamic b values for SDXL Turbo
36
Comparing different b1, b2 values for SDXL Turbo
37
Dynamic s values for SDXL Turbo
38
Final comparison of all results so far
Description:
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.

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

kasukanra
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