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How To Do Stable Diffusion XL (SDXL) DreamBooth Training For Free ‐ Utilizing Kaggle ‐ Easy Tutorial

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Furkan Gözükara edited this page Jul 3, 2024 · 4 revisions

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Tutorial Link : https://youtu.be/16-b1AjvyBE

How To Do Stable Diffusion XL (SDXL) DreamBooth Training For Free - Utilizing Kaggle - Easy Tutorial

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🌟 Master Stable Diffusion XL Training on Kaggle for Free! 🌟 Welcome to this comprehensive tutorial where I'll be guiding you through the exciting world of setting up and training Stable Diffusion XL (SDXL) with Kohya on a free Kaggle account. This video is your one-stop resource for learning everything from initiating a Kaggle session with dual T4 GPUs to fine-tuning your SDXL model for optimal performance.

#Kaggle #StableDiffusion #SDXL

Notebook ⤵️

Tutorial GitHub Readme File ⤵️

Tutorial Video Chapters

  • 0:00 Introduction To The Kaggle Free SDXL DreamBooth Training Tutorial
  • 2:01 How to register Kaggle account and login
  • 2:26 Where to and how to download Kaggle training notebook for Kohya GUI
  • 2:47 How to import / load downloaded Kaggle Kohya GUI training notebook
  • 3:08 How to enable GPUs and Internet on your Kaggle session
  • 3:52 How to start your Kaggle session / cloud machine
  • 4:02 How to see your Kaggle given free hardware features
  • 4:18 How to install Kohya GUI on a Kaggle notebook
  • 4:46 How to know when the Kohya GUI installation has been completed on a Kaggle notebook
  • 5:00 How to download regularization images before starting training
  • 5:22 Introduction to the classification dataset that I prepared
  • 6:35 How to setup and enter your token to use Kohya Web UI on Kaggle
  • 8:20 How to load pre-prepared configuration json file on Kohya GUI
  • 8:48 How to do Dataset Preparation after configuration loaded
  • 8:59 How to upload your training dataset to your Kaggle session
  • 9:12 Properties of my training images dataset
  • 9:22 What kind of training dataset is good and why
  • 10:06 How to upload any data to Kaggle and use it on your notebook
  • 10:20 How to use previously composed Kaggle dataset in your new Kaggle session
  • 10:34 How to get path of session included dataset
  • 10:44 Why do I train with 100 repeating and 1 epoch
  • 10:54 Explanation of 1 epoch and how to calculate epochs
  • 11:23 How to set path of regularization images
  • 11:33 How to set instance prompt and why we set it to a rare token
  • 11:46 How to set destination directory and model output into temp disk space
  • 12:29 How to set Kaggle temporary models folder path
  • 13:07 How many GB temporary space do Kaggle provides us for free
  • 13:23 Which parameters you need to set on Kohya GUI before starting training
  • 13:33 How to calculate the N number of save every N steps parameter to save checkpoints
  • 13:45 How to calculate total number of steps that your Kohya Stable Diffusion going to take
  • 14:10 If I want to take 5 checkpoints what number of steps I need calculation
  • 14:33 How to download saved configuration json file
  • 14:43 Click start training and training starts
  • 14:55 Can we combine both GPU VRAM and use as a single VRAM
  • 15:05 How we are setting the base model that it will do training
  • 15:55 The SDXL full DreamBooth training speed we get on a free Kaggle notebook
  • 16:51 Can you close your browser or computer during training
  • 17:54 Can we download models during training
  • 18:26 Training has been completed
  • 18:57 How to prevent last checkpoint to be saved 2 times
  • 19:30 How to download generated checkpoints / model files
  • 21:11 How you will know the download status when downloading from Kaggle working directory
  • 22:03 How to upload generated checkpoints / model files into Hugging Face for blazing fast upload and download
  • 25:02 Where to find Hugging Face uploaded models after upload has been completed
  • 26:54 Explanation of why generated last 2 checkpoints are duplicate
  • 27:27 Hugging Face upload started and the amazing speed of the upload
  • 27:49 All uploads have been completed now how to download them
  • 29:02 Download speed from Hugging Face repository
  • 29:17 How to terminate your Kaggle session
  • 29:36 Where to see how much GPU time you have left for free on Kaggle for that week
  • 29:46 How to make a fresh installation of Automatic1111 SD Web UI
  • 31:05 How to download Hugging Face uploaded models with wget very fast
  • 31:57 Which settings to set on a freshly installed Automatic1111 Web UI, e.g. VAE quick selection
  • 32:07 How to install after detailer (adetailer) extension to improve faces automatically
  • 32:51 Why you should add --no-half-vae to your command line arguments
  • 33:05 How to start / restart Automatic1111 Web UI
  • 33:37 How switch to the development branch of Automatic1111 Web UI to use latest version
  • 34:24 Where to download amazing prompts list for DreamBooth trained models
  • 35:07 How to use PNG info to quickly load prompts
  • 35:52 How to do x/y/z checkpoint comparison to find the best checkpoint of your SDXL DreamBooth training
  • 38:09 How to make SDXL work faster on weak GPUs
  • 38:37 How to analyze results of x/y/z checkpoint comparison to decide best checkpoint
  • 42:06 How to obtain better images
  • 42:20 How to install TensorRT and use it to generate images very fast with same quality
  • 44:41 How to use amazing prompt list as a list txt file
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