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Full Stable Diffusion SD & XL Fine Tuning Tutorial With OneTrainer On Windows & Cloud ‐ Zero To Hero
Full Stable Diffusion SD & XL Fine Tuning Tutorial With OneTrainer On Windows & Cloud - Zero To Hero
The description of the video is as below
In this tutorial, I am going to show you how to install OneTrainer from scratch on your computer and do a Stable Diffusion SDXL (Full Fine-Tuning 10.3 GB VRAM) and SD 1.5 (Full Fine-Tuning 7GB VRAM) based models training on your computer and also do the same training on a very cheap cloud machine from MassedCompute if you don't have such computer.
Tutorial Readme File
Register Massed Compute From Below Link (could be necessary to use our Special Coupon for A6000 GPU for 31 cents per hour)
- https://bit.ly/SECoursesMassedCompute
- https://vm.massedcompute.com/signup?linkId=lp_034338&sourceId=secourses&tenantId=massed-compute
Coupon Code for A6000 GPU is : SECourses
- 0:00 Introduction to Zero-to-Hero Stable Diffusion (SD) Fine-Tuning with OneTrainer (OT) tutorial
- 3:54 Intro to instructions GitHub readme
- 4:32 How to register Massed Compute (MC) and start virtual machine (VM)
- 5:48 Which template to choose on MC
- 6:36 How to apply MC coupon
- 8:41 How to install OT on your computer to train
- 9:15 How to verify your Python, Git, FFmpeg and Git installation
- 12:00 How to install ThinLinc and start using your MC VM
- 12:26 How to setup folder synchronization and file sharing between your computer and MC VM
- 13:56 End existing session in ThinClient
- 14:06 How to turn off MC VM
- 14:24 How to connect and start using VM
- 14:41 When use end existing session
- 16:38 How to download very best OT preset training configuration for SD 1.5 & SDXL models
- 18:00 How to load configuration preset
- 18:38 Full explanation of OT configuration and best hyper parameters for SDXL
- 24:10 How to setup training concepts accurately in OT
- 24:52 How to caption images for SD training
- 30:17 Why my training images dataset is not great and what is a better dataset
- 31:41 How to make DreamBooth effect in OT with regularization images concept
- 32:44 Effect of using ground truth regularization images dataset
- 34:41 How to set regularization images repeating
- 35:55 Explanation of training tab configuration and parameters
- 41:58 What does masked training do and how to do masked training and generate masks
- 44:53 Generate samples during training setup
- 46:05 How to save checkpoints during training to compare and find best one later
- 47:11 How to save your configuration in OT
- 47:22 How to install and utilize nvitop to see VRAM usage
- 48:06 Why super slow training happens due to shared VRAM and how to fix it
- 48:40 How to reduce VRAM usage before starting training
- 49:01 Start training on Windows
- 49:11 Starting to setup everything on MC same as on Windows
- 49:37 Upload data to MC
- 51:11 Update OT on MC
- 52:33 How to download regularization images
- 53:42 How to minimize all windows on MC
- 54:00 Start OT on MC
- 54:20 Setting everything on MC same as Windows
- 55:22 How to set folders on MC VM
- 56:31 How to properly crop and resize your training images
- 57:47 Accurate Auto1111 Models folder on MC
- 58:05 Copy file & folder path on MC
- 58:54 All of the rest of the config on MC
- 1:03:29 How to utilize second GPU if you have
- 1:05:45 Checking back again our Windows training
- 1:06:06 How to use Automatic1111 (A1111) SD Web UI on MC and Windows
- 1:11:35 How to use default Python on MC
- 1:11:55 Checking training speed and explaining what it means
- 1:12:13 How many steps we are going to train explanation
- 1:13:40 First checkpoint and howe checkpoints named
- 1:14:15 How to fix A1111 errors
- 1:15:44 How to start A1111 Web UI and use it with Gradio Live share and locally
- 1:17:45 What to do if model loading takes forever on Gradio and how to fix it
- 1:19:01 Where to see status of the training of OT
- 1:19:43 How to upload checkpoints / anything into Hugging Face for permanently saving
- 1:26:21 How to auto upgrade A1111 and install ADetailer and ControlNet extensions
- 1:29:10 How to use trained model checkpoints on Massed Compute
- 1:30:08 How to test checkpoints to find best one
- 1:32:15 Why you should use After Detailer (adetailer) and how to use it properly
- 1:34:48 How to do proper highres fix upscale
- 1:36:19 Why anatomy inaccuracy happens
- 1:37:07 How to generate images forever in A1111
- 1:38:02 Where the generated images are saved and download them
- 1:40:30 Super Important
- 1:45:16 Analyzing x/y/z checkpoint comparison results to find best checkpoint
- 1:48:20 How to understand if model is overtrained
- 1:52:27 How to generate different expressions having photos
- 1:54:53 How to do inpainting in Stable Diffusion A1111
- 1:56:34 How to generate LoRA from your trained checkpoint
- 1:58:03 Windows OneTrainer training completed so how to use them on your computer
- 2:00:24 Best SD 1.5 models Fine-Tuning / DreamBooth training configuration / hyper-parameters
- 2:03:50 How can you know you have sufficient VRAM?
- 2:05:36 What to do before terminating MC VM
- 2:06:55 How to terminate your VM to not spend anymore money
- 2:08:35 How to do style, object, etc training
- 2:09:47 What to do if your thin client don't synch