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Intro

Required resources

LyCORIS overview

LoCon training settings

redjuice LoCon Epoch vs. Weight grid analysis 32 dims

redjuice LoCon Epoch vs. Weight grid analysis 40 dims

Vanilla LoRA

Explaining how I finalized my hyperparameters

LoHa training settings

redjuice LoHa grid analysis Conv. Dim = 4, Conv. Alpha = 2

redjuice LoHa grid analysis Conv. Dim = 4, Conv. Alpha = 1

swd3e2 style dataset overview

BooruDatasetTagManager

swd3e2 LoCon grid analysis 40 dims

swd3e2 LoHa grid analysis Conv. Dim = 4, Conv. Alpha = 1

Adjusting LoHa hyperparameters Part 1

swd3e2 LoHa grid analysis, Conv. Dim = 4, Conv. Alpha = 2, Adam8Wbit, fixed initial learning rate

Adjusting LoHa hyperparameters Part 2

swd3e2 LoHa grid analysis, Conv. Dim = 14, Conv. Alpha = 14, DAdaptation

Closing thoughts

Description:

Dive into an in-depth tutorial on using LyCORIS for style training in Stable Diffusion, focusing on LoCon and LoHa techniques as an extension of LoRA. Learn about required resources, LyCORIS overview, and detailed training settings for both LoCon and LoHa. Explore grid analyses comparing epochs and weights for different dimensions, and understand how to finalize hyperparameters. Discover the process of creating and managing style datasets using tools like BooruDatasetTagManager. Follow along as various grid analyses are performed for different artists' styles, and gain insights into adjusting LoHa hyperparameters for optimal results. Conclude with valuable closing thoughts on implementing these advanced techniques in your AI art creation process.

Stable Diffusion- LyCORIS for Style - LoRA Part 2

kasukanra

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#Computer Science #Deep Learning #Stable Diffusion #Machine Learning #LoRA (Low-Rank Adaptation) #Art & Design #Character Design #Visual Arts #Digital Art #Concept Art #Design & Creativity #Graphic Design #Digital Illustration

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