Learn how to replicate any artistic style using AI Stable Diffusion and LORA in this comprehensive 42-minute tutorial. Master the process of training SDXL with your own images using the Kohya GUI tool, covering everything from dataset preparation and image captioning to selecting optimal training parameters. Explore techniques for upscaling images, creating training folders, and setting up instance and class prompts. Dive into advanced topics such as regularization, learning rates, and network configurations. Discover GPU solutions and RunPod setup for efficient LORA training. By the end, gain the expertise to train any style you desire, whether you're a beginner or an experienced user.
Overview
Syllabus
Train SDXL with LORA
What is LORA?
Koya SS GUI
Image Dataset preparation
Find good video game images on Steam
Upscale images sharper with Stable Diffusion
Make sure images are not too big for LORA Training
SDXL LORA Training Folder Creation
Instance Prompt
Find the right style for LORA Training
Class Prompt
LORA Repeats Training Steps
Regularization images
Training Data
LORA Image Captioning
How to replace a word in multiple text files on Windows
The right SDXL STYLE LORA Training Parameters
LORA Type Standard vs LoCON or LoHA LyCORIS
Train Batch size
Number of Epoch Training
BF16 & FP16 & Cache
The RIGHT Learning Rate for SDXL STYLE LORA
SDXL Image Resolution & Buckets
LORA Network Rank & Network alpha
Gradient Accumulate Steps LORA
Noise Offset LORA
LORA Training & VRAM Usage
GPU Solutions & RunPod
Runpod Setup for LORA Training
Runpod Template LORA Update
How to select the right LORA Model?
Chose the final Model
Conclusion on LORA STYLE Training
Taught by
Aitrepreneur
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