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Stable Diffusion XL DreamBooth Training on Kaggle - Free Tutorial

Software Engineering Courses - SE Courses via YouTube

Overview

Learn to set up and train Stable Diffusion XL (SDXL) with Kohya on a free Kaggle account in this comprehensive 52-minute tutorial. Master the process of initiating a Kaggle session with dual T4 GPUs, preparing datasets, configuring training parameters, and fine-tuning SDXL models. Discover how to utilize Kaggle's free resources, upload and download models, integrate with Hugging Face for efficient file management, and implement Automatic1111 SD Web UI for image generation. Explore advanced techniques such as checkpoint comparison, TensorRT installation for faster image generation, and effective prompt list usage to enhance your AI image creation skills.

Syllabus

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

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Software Engineering Courses - SE Courses

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