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