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Zero To Hero Generative AI - Become A Master

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  1. Lecture 1 : How To Install Python, Setup Virtual Environment VENV, Set Default Python System Path & Install Git
  2. Lecture 3 : Zero to Hero ControlNet Tutorial: Stable Diffusion Web UI Extension | Complete Feature Guide
  3. Lecture 4 : How To Find Best Stable Diffusion Generated Images By Using DeepFace AI - DreamBooth / LoRA Training
  4. Lecture 5 : Generate Studio Quality Realistic Photos By Kohya LoRA Stable Diffusion Training - Full Tutorial
  5. Lecture 6 : The END of Photography - Use AI to Make Your Own Studio Photos, FREE Via DreamBooth Training
  6. Lecture 7 : How To Use Stable Diffusion X-Large (SDXL) On Google Colab For Free
  7. Lecture 8 : Stable Diffusion XL (SDXL) Locally On Your PC - 8GB VRAM - Easy Tutorial With Automatic Installer
  8. Lecture 9 : Ultimate RunPod Tutorial For Stable Diffusion - Automatic1111 - Data Transfers, Extensions, CivitAI
  9. Lecture 10 : How To Use SDXL On RunPod Tutorial. Auto Installer & Refiner & Amazing Native Diffusers Based Gradio
  10. Lecture 11 : ComfyUI Tutorial - How to Install ComfyUI on Windows, RunPod & Google Colab | Stable Diffusion SDXL
  11. Lecture 12 : First Ever SDXL Training With Kohya LoRA - Stable Diffusion XL Training Will Replace Older Models
  12. Lecture 13 : How To Use SDXL in Automatic1111 Web UI - SD Web UI vs ComfyUI - Easy Local Install Tutorial / Guide
  13. Lecture 14 : Mind-Blowing Deepfake Tutorial: Turn Anyone into Your Favorite Movie Star! PC & Google Colab - roop
  14. Lecture 15 : How to use Stable Diffusion X-Large (SDXL) with Automatic1111 Web UI on RunPod - Easy Tutorial
  15. Lecture 16 : Become A Master Of SDXL Training With Kohya SS LoRAs - Combine Power Of Automatic1111 & SDXL LoRAs
  16. Lecture 17 : How To Do SDXL LoRA Training On RunPod With Kohya SS GUI Trainer & Use LoRAs With Automatic1111 UI
  17. Lecture 18 : How to Do SDXL Training For FREE with Kohya LoRA - Kaggle - NO GPU Required - Pwns Google Colab
  18. Lecture 19 : How Use Stable Diffusion, SDXL, ControlNet, LoRAs For FREE Without A GPU On Kaggle Like Google Colab
  19. Lecture 20 : Turn Videos Into Animation With Just 1 Click - ReRender A Video Tutorial
  20. Lecture 21 : Turn Videos Into Animation / 3D Just 1 Click - ReRender A Video Tutorial - Installer For RunPod
  21. Lecture 22 : Double Your Stable Diffusion Inference Speed with RTX Acceleration TensorRT: A Comprehensive Guide
  22. Lecture 23 : How to Install & Run TensorRT on RunPod, Unix, Linux for 2x Faster Stable Diffusion Inference Speed
  23. Lecture 24 : SOTA Image PreProcessing Scripts For Stable Diffusion Training - Auto Subject Crop & Face Focus
  24. Lecture 25 : Fooocus Stable Diffusion Web UI - Use SDXL Like You Are Using Midjourney - Easy To Use High Quality
  25. Lecture 26 : How To Do Stable Diffusion XL (SDXL) DreamBooth Training For Free - Utilizing Kaggle - Easy Tutorial
  26. Lecture 2 : Essential AI Tools and Libraries: A Guide to Python, Git, C++ Compile Tools, FFmpeg, CUDA, PyTorch
  27. Lecture 27 : Essential AI Tools and Libraries: A Guide to Python, Git, C++ Compile Tools, FFmpeg, CUDA, PyTorch
Lesson 15 of 27
In Progress

Lecture 16 : Become A Master Of SDXL Training With Kohya SS LoRAs – Combine Power Of Automatic1111 & SDXL LoRAs

icarus November 10, 2023

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In this tutorial, you will learn how to install Automatic1111 Web UI for SDXL. How to use LoRAs with Automatic1111 SD Web UI. How to install Kohya SS GUI scripts to do Stable Diffusion training. How to train LoRAs on SDXL model with least amount of VRAM using settings. All of the details, tips and tricks of Kohya trainings. How to do x/y/z plot comparison to find your best LoRA checkpoint. And many more.

Tutorial GitHub Readme File ⤵️

0:00 Intro
2:15 Pre-requirements of this tutorial
3:20 1-Click installer for Automatic1111 Web UI
4:00 How to install Automatic1111 Web UI for SDXL and SD 1.5 models
4:15 How to checkout and verify your installed Python version
4:51 Which Automatic1111 Web UI command line arguments you need for SDXL
5:15 Where to find all command line arguments of Automatic1111 Web UI
5:45 Where to download SDXL model files and VAE file
6:17 Which folders you need to put model and VAE files
7:21 Detailed explanation of what is VAE (Variational Autoencoder) of Stable Diffusion
7:57 How to set your VAE and enable quick VAE selection options in Automatic1111
8:22 What does Automatic and None options mean in SD VAE selection
8:43 Why you shouldn’t use embedded VAE of SD 1.0 model
9:38 Correct resolution of SDXL – how to use SDXL
9:58 How to install Kohya SS GUI script for SDXL training
12:29 What to do if your CMD is not progressing
13:19 When you need to use FP16 instead of BF16
13:55 How to install Kohya on RunPod or on a Unix system
14:35 How to start Kohya GUI after installation
15:18 What are Stable Diffusion LoRA and DreamBooth (rare token, class token, and more) training
15:45 How to select SDXL model for LoRA training in Kohya GUI
16:31 How to save and load your Kohya SS training configuration
16:41 How to use my own used configuration for this tutorial video training
17:56 How to prepare your training images for Kohya LoRA or DreamBooth SDXL training
19:17 What kind of training images you should use for training
20:57 What kind of regularization images you should use? The logic of using ground truth images
24:35 What is number of repeating in Kohya SS. Which number you need to pick
25:56 Where will be your LoRA checkpoints saved
26:31 How to verify your training images dataset properly composed
27:12 How to set your generated LoRA file names
27:46 Which training parameters you should use for SDXL LoRA training
27:56 Why select train batch size 1 and gradient accumulation steps 1
28:18 The logic of number of epochs
30:25 Detailed explanation of Kohya SS training. What each parameter and option do
31:03 Which learning rate for SDXL Kohya LoRA training
31:10 Why do I use Adafactor
32:39 The rest of training settings
33:56 Which Network Rank (Dimension) you need to select and why
34:44 How to fix if you get out of VRAM error – not enough memory
36:04 What is Network Alpha of Kohya LoRA
36:35 Don’t forget Gradient Checkpointing
37:07 How to continue training with Kohya LoRA training
37:42 What does print training command do
37:59 How to calculate number of steps for each Epoch
38:12 How to calculate how many regularization images you need
38:43 When you should increase batch size when doing Stable Diffusion training?
39:27 How number of total steps (max training steps) are calculated in Kohya training
40:25 How you can generate your own regularization / classification images
41:45 How to manually edit generated Kohya training command and execute it
43:21 How to start training in Kohya
43:36 How to do training on your second GPU with Kohya SS
46:31 How much VRAM is SDXL LoRA training using with Network Rank (Dimension) 32
47:15 SDXL LoRA training speed of RTX 3060
47:25 How to fix image file is truncated error
48:05 How to reach and contact me if you get an error
48:50 VRAM usage and speed testing of different Network Rank
51:40 How to use absolute min VRAM to make it work
52:16 When is first checkpoint generated and where they are saved
53:12 How to continue training from saved state
53:55 Auto saved configuration files
55:42 How to use LoRAs with Automatic1111 Web UI
58:02 How to assign previews to your LoRA files / checkpoints
59:00 How to do x/y/z LoRA checkpoint comparison to find best LoRA model
1:03:10 How to understand if your LoRA model is overtrained / cooked or not
1:04:50 Testing our LoRAs stylization capability
1:07:07 How to generate studio shot quality images that you can use on LinkedIn, Twitter, Instagram and such
1:07:40 How to find best generated images with using an AI tool
1:11:42 How to utilize ChatGPT to find very good prompts
1:12:19 How to utilize high-res fix and LoRA inpainting to get amazing quality distant shot images
1:16:02 How to fix hands and face
1:19:52 How to use same training command I used
1:20:29 When you need to reduce weight / emphasis of the rare token
1:23:24 How to join our Discord community for help and tips