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Introduction

List of SD3 training repositories

Method of approach

kohya sd-scripts environment setup

.toml file setup

SDPA

Multiresolution noise

Timesteps

.toml miscellaneous

Creating the meta_cap.json

sd-scripts sd3 parameters

sd3 pretrained model path

kohya sd3 readme

sd3 sampler settings

sd3 SDPA

Prodigy settings

Dependency issues

Actually running the training

How to run sd3 workflow/test model

kohya sd3 commit hash

Now what?

SD3 AdamW8Bit

wandb proof

Is it over?

Hindsight training appendix

Upper bound of sd3 LR 1.5e-3 for kohya exploding gradient

1.5e-4

SimpleTuner quickstart

SimpleTuner environment setup

Setting up CLI logins

SD3 environment overview

Dataset settings overview

Dataset settings hands-on

multidatabackend.json

SimpleTuner documentation

sdxl_env.sh

Model name

Remaining settings

train_sdxl.sh

Diffusers vs. Checkpoints

Symlinking models

ComfyUI UNET loader

Initial explorations overfitting?

Environment art overfitting?

Character Art Overfitting evaluation

Trying short prompts

ODE samplers

Testing other prompts

How to generate qualitative grids

Generating grids through API workflow

8e-6

Analyzing wandb

Higher LR 1.5e-5

Ablation study #1

Ablation study #2

Ablation study #3

SimpleTuner LoRA setup

Adding lora_rank/lora_alpha to accelerate launch

LoRA failed qualitative grids LoRA rank/alpha = 16

Exploding gradient LR = 1.5e-3

LR = 4e-4 #1

LR = 4e-4 #2

LR = 6.5e-4

Finetune vs. LoRA #1

Finetune vs. LoRA #2

Finetune vs. LoRA environment

Conclusion

Description:

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Dive into an extensive 80-minute tutorial on training Stable Diffusion 3 2B Medium using kohya and SimpleTuner for full finetune and LoRA. Follow along as the process of art style training is documented, including experiments, mistakes, and analysis of results. Learn about environment setup, parameter configuration, and various training approaches. Explore topics such as SDPA, multiresolution noise, timesteps, and prodigy settings. Gain insights into troubleshooting dependency issues, running workflows, and testing models. Compare different learning rates, analyze results using Weights & Biases, and understand the differences between finetuning and LoRA. Benefit from practical tools, theoretical discussions, and real-world examples to enhance your understanding of SD3 training for art styles, concepts, and subjects.

Stable Diffusion 3 2B Medium Training with Kohya and SimpleTuner - Full Finetune and LoRA

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#Computer Science #Deep Learning #Stable Diffusion #Machine Learning #Artificial Intelligence #Neural Networks #Hyperparameter Optimization #LoRA (Low-Rank Adaptation) #Computer Vision #Image Generation #Fine-Tuning #AI Image Generation #ComfyUI