How to Do SDXL Training with Kohya LoRA - Kaggle - No GPU Required

How to Do SDXL Training with Kohya LoRA - Kaggle - No GPU Required

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Introduction to how to do amazing FREE training of Stable Diffusion XL without owning a GPU

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1 of 53

Introduction to how to do amazing FREE training of Stable Diffusion XL without owning a GPU

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How to Do SDXL Training with Kohya LoRA - Kaggle - No GPU Required

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  1. 1 Introduction to how to do amazing FREE training of Stable Diffusion XL without owning a GPU
  2. 2 How to register Kaggle to get a free account to do free training
  3. 3 How to verify your phone number in Kaggle to be able to use cloud GPUs for free
  4. 4 How to generate a Kaggle notebook and start Stable Diffusion XL free Kohya SS LoRA training
  5. 5 How to download and import SDXL LoRA training notebook
  6. 6 How to properly with correct config start session on Kaggle to begin training
  7. 7 How to enable GPU on Kaggle
  8. 8 How to see how much GPU time you have used and how much you have left on Kaggle
  9. 9 How to look at used resources in your Kaggle session such as disk space, GPU, CPU, RAM
  10. 10 How to clone Kohya SS GUI and install it on a free Kaggle notebook
  11. 11 How to understand and use pathing structure of Kaggle
  12. 12 Where is our root / working directory in Kaggle
  13. 13 How to know when the installation of Kohya SS GUI has been completed
  14. 14 How to download ground truth regularization / classification images
  15. 15 How to upload your regularization / classification images and use them
  16. 16 How to use your previously uploaded images / datasets in your Kaggle training sessions
  17. 17 How to start Kohya SS GUI on Kaggle notebook
  18. 18 How to access started Kohya SS GUI instance via publicly given Gradio link
  19. 19 Starting to setup Kohya SDXL LoRA training parameters and settings
  20. 20 Which source model we need to use for SDXL training a free Kaggle notebook
  21. 21 How to prepare training dataset easily with dataset preparation feature of Kohya SS GUI
  22. 22 How to upload your training images and prepare them for SDXL training
  23. 23 How get and set folder path of training and regularization / classification images
  24. 24 Where to and how to save training results and how to generate training folders
  25. 25 How to copy info to folders tab
  26. 26 Setting up all training parameters
  27. 27 Network Rank Dimension trade-off
  28. 28 Continuing to setting up all training parameters
  29. 29 How to start training after everything is set
  30. 30 What is the formula of calculating number of training total steps
  31. 31 How to execute training command
  32. 32 How to calculate necessary number of classification / regularization images that you need
  33. 33 Training started
  34. 34 Why it shows total number of epochs double of the number we did set
  35. 35 Where is our SDXL LoRA training checkpoints are saved and how to download them
  36. 36 Why generated safetensor files, checkpoints are 228 MBs
  37. 37 How to enable allow multiple files download in your browser to download generated LoRA checkpoints
  38. 38 How to download all of the checkpoints as a single file - zip them all
  39. 39 How to download LoRA safetensors folder entirely
  40. 40 How to extract and open downloaded as zip LoRA checkpoints
  41. 41 How to save your LoRA checkpoints on your Kaggle account to use later
  42. 42 How to use your trained LoRA checkpoints in your Automatic1111 Web UI on your PC
  43. 43 How to download and use 750 styles containing styles.csv file
  44. 44 How to find best checkpoint of your Kohya SDXL LoRA training
  45. 45 How to see used prompts and settings of generated images via png info tab of Automatic1111 Web UI
  46. 46 How did I decide to use the certain checkpoint via x/y/z script of Automatic1111 Web UI
  47. 47 How to use your LoRAs in Automatic1111 Web UI
  48. 48 How to select your LoRA from the interface
  49. 49 How to generate same batch with correct seed, how batch seed is determined
  50. 50 How to install after detailer adetailer extension to improve faces in your generations automatically
  51. 51 After detailer extension enabled comparison results
  52. 52 How to get amazing likeness - realism having images of your trained subject,
  53. 53 How to find best amazing among thousands of generated images by using DeepFace AI similarity script

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