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Full Stable Diffusion SD & XL Fine Tuning Tutorial With OneTrainer On Windows & Cloud ‐ Zero To Hero

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Furkan Gözükara edited this page Apr 14, 2024 · 2 revisions

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Full Stable Diffusion SD & XL Fine Tuning Tutorial With OneTrainer On Windows & Cloud - Zero To Hero

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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) ⤵️

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
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