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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 17 of 27
In Progress

Lecture 18 : How to Do SDXL Training For FREE with Kohya LoRA – Kaggle – NO GPU Required – Pwns Google Colab

icarus November 10, 2023

If you don’t have a strong GPU for Stable Diffusion XL training then this is the tutorial you are looking for. We will use Kaggle free notebook to do Kohya SDXL LoRA training. In this tutorial you will master Kohya SDXL with Kaggle! 🚀 Curious about training Kohya SDXL? Learn why Kaggle outshines Google Colab! We will uncover the power of free Kaggle’s dual GPU. 🔥 Step-by-step guide inside! Boost your skills and make the most of FREE Kaggle resources! 💡 #Training #SDXL #Kaggle

Kaggle Kohya SDXL Notebook File ⤵️

Tutorial GitHub Readme File ⤵️

SECourses Discord To Get Full Support ⤵️

0:00 Introduction to how to do amazing FREE training of Stable Diffusion XL without owning a GPU
2:35 How to register Kaggle to get a free account to do free training
3:05 How to verify your phone number in Kaggle to be able to use cloud GPUs for free
3:55 How to generate a Kaggle notebook and start Stable Diffusion XL free Kohya SS LoRA training
4:20 How to download and import SDXL LoRA training notebook
5:46 How to properly with correct config start session on Kaggle to begin training
5:56 How to enable GPU on Kaggle
6:34 How to see how much GPU time you have used and how much you have left on Kaggle
6:49 How to look at used resources in your Kaggle session such as disk space, GPU, CPU, RAM
7:00 How to clone Kohya SS GUI and install it on a free Kaggle notebook
7:21 How to understand and use pathing structure of Kaggle
7:37 Where is our root / working directory in Kaggle
9:57 How to know when the installation of Kohya SS GUI has been completed
10:14 How to download ground truth regularization / classification images
13:17 How to upload your regularization / classification images and use them
14:13 How to use your previously uploaded images / datasets in your Kaggle training sessions
16:00 How to start Kohya SS GUI on Kaggle notebook
16:31 How to access started Kohya SS GUI instance via publicly given Gradio link
17:09 Starting to setup Kohya SDXL LoRA training parameters and settings
17:40 Which source model we need to use for SDXL training a free Kaggle notebook
18:55 How to prepare training dataset easily with dataset preparation feature of Kohya SS GUI
19:26 How to upload your training images and prepare them for SDXL training
20:25 How get and set folder path of training and regularization / classification images
20:51 Where to and how to save training results and how to generate training folders
21:44 How to copy info to folders tab
22:09 Setting up all training parameters
23:44 Network Rank Dimension trade-off
24:44 Continuing to setting up all training parameters
25:54 How to start training after everything is set
26:54 What is the formula of calculating number of training total steps
27:54 How to execute training command
29:10 How to calculate necessary number of classification / regularization images that you need
31:05 Training started
31:24 Why it shows total number of epochs double of the number we did set
32:10 Where is our SDXL LoRA training checkpoints are saved and how to download them
33:07 Why generated safetensor files, checkpoints are 228 MBs
33:27 How to enable allow multiple files download in your browser to download generated LoRA checkpoints
33:37 How to download all of the checkpoints as a single file – zip them all
34:27 How to download LoRA safetensors folder entirely
35:04 How to extract and open downloaded as zip LoRA checkpoints
36:48 How to save your LoRA checkpoints on your Kaggle account to use later
37:50 How to use your trained LoRA checkpoints in your Automatic1111 Web UI on your PC
38:50 How to download and use 750 styles containing styles.csv file
39:40 How to find best checkpoint of your Kohya SDXL LoRA training
40:07 How to see used prompts and settings of generated images via png info tab of Automatic1111 Web UI
40:26 How did I decide to use the certain checkpoint via x/y/z script of Automatic1111 Web UI
41:08 How to use your LoRAs in Automatic1111 Web UI
42:08 How to select your LoRA from the interface
44:04 How to generate same batch with correct seed, how batch seed is determined
44:38 How to install after detailer (adetailer) extension to improve faces in your generations automatically
45:07 After detailer extension enabled comparison results
46:01 How to get amazing likeness – realism having images of your trained subject,
46:27 How to find best amazing among thousands of generated images by using DeepFace AI similarity script