LORA training guide/tutorial so you can understand how to use the important parameters on KohyaSS.
Train in minutes with Dreamlook.AI: https://dreamlook.ai/?via=N4T
code: "NOT4TALENT"
Join our Discord server: https://discord.gg/FWPkVbgYyK (Amazing people like LeFourbe on there)
------------- Links used in the VIDEO ----------
Folder to JSON Script: https://drive.google.com/drive/folders/1xW4SFCXi8iX0bN4--zH2A-cvv_1Ah1Zg?usp=sharing
KohyaSS: https://github.com/bmaltais/kohya_ss
Fastest Model training: https://dreamlook.ai
Alpha Rank and Dim post by @AsheJunius https://ashejunius.com/alpha-and-dimensions-two-wild-settings-of-training-lora-in-stable-diffusion-d7ad3e3a3b0a
Google Colabs for "free" training: https://github.com/camenduru/stable-diffusion-webui-colab/tree/training#-community-kohya-ss--training-colabs-gpu
https://colab.research.google.com/github/Linaqruf/kohya-trainer/blob/main/kohya-LoRA-dreambooth.ipynb
Super detailed LORA training guide by: "The Other Lora Rentry Guy" ?: https://rentry.co/59xed3#preamble
BooruDatasetTagManager: https://github.com/starik222/BooruDatasetTagManager/releases/tag/v1.6.5
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0:00 intro
0:10 What we need
0:23 Install KohyaSS
1:38 Thanks to LeFourbe
1:54 What are LORA
2:35 Best Datasets
4:26 How to get the images
5:06 Best Captioning
6:32 Captioning but AI POV
9:38 Captioning Example
11:00 Using BooruDatasetTagmanager
13:10 Training decisions
13:25 Choosing a model
14:02 Folder Structure making
14:32 What Regularization does
15:06 Steps and epochs Explained
16:50 Aprox recommendation
17:00 Ill use 14 steps and 6 epochs
17:32 Creating the folders
18:00 Training Parameters
19:25 Learning Rate Explained
20:40 LR scheduler
21:02 Use AdamW or AdamW8bit
21:30 Network Rank and Alpha
22:10 Resolution and Bucketing
23:10 Advanced Options
24:05 Train AI in minutes (sponsored)
26:10 Test Results
27:23 Thanks for watching :3