How to Do SDXL Training For FREE with Kohya LoRA - Kaggle - NO GPU Required - Pwns Google Colab
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 ⤵️
https://www.patreon.com/posts/kohya-sdxl-lora-88397937
Tutorial GitHub Readme File ⤵️
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