Full Training Tutorial and Guide and Research For a FLUX Style
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4
Furkan Gözükara
MonsterMMORPG
AI & ML interests
Check out my youtube page SECourses for Stable Diffusion tutorials. They will help you tremendously in every topic
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Posts
39
Post
2735
Huge FLUX LoRA vs Fine Tuning / DreamBooth Experiments Completed, Moreover Batch Size 1 vs 7 Fully Tested as Well, Not Only for Realism But Also for Stylization - 15 vs 256 images having datasets compared as well (expressions / emotions tested too) - Used Kohya GUI for training
Full files and article : https://www.patreon.com/posts/112099700
Download images in full resolution to see prompts and model names
All trainings are done with Kohya GUI, perfectly can be done locally on Windows, and all trainings were 1024x1024 pixels
Fine Tuning / DreamBooth works as low as 6 GB GPUs (0 quality degrade totally same as 48 GB config)
Best quality of LoRA requires 48 GB GPUs , 24 GB also works really good and minimum 8 GB GPU is necessary for LoRA (lots of quality degrade)
Full size grids are also shared for the followings: https://www.patreon.com/posts/112099700
Additionally, I have shared full training entire logs that you can see each checkpoint took time. I have shared best checkpoints, their step count and took time according to being either LoRA, Fine Tuning or Batch size 1 or 7 or 15 images or 256 images, so a very detailed article regarding completed.
Check the images to see all shared files in the post.
Furthermore, a very very detailed analysis having article written and all latest DreamBooth / Fine Tuning configs and LoRA configs are shared with Kohya GUI installers for both Windows, Runpod and Massed Compute.
Moreover, I have shared new 28 realism and 37 stylization testing prompts.
Current tutorials are as below:
Windows requirements CUDA, Python, cuDNN, and such : https://youtu.be/DrhUHnYfwC0
How to use SwarmUI : https://youtu.be/HKX8_F1Er_w
How to use FLUX on SwarmUI : https://youtu.be/bupRePUOA18
How to use Kohya GUI for FLUX training : https://youtu.be/nySGu12Y05k
How to use Kohya GUI for FLUX training on Cloud (RunPod and Massed Compute) : https://youtu.be/-uhL2nW7Ddw
Full files and article : https://www.patreon.com/posts/112099700
Download images in full resolution to see prompts and model names
All trainings are done with Kohya GUI, perfectly can be done locally on Windows, and all trainings were 1024x1024 pixels
Fine Tuning / DreamBooth works as low as 6 GB GPUs (0 quality degrade totally same as 48 GB config)
Best quality of LoRA requires 48 GB GPUs , 24 GB also works really good and minimum 8 GB GPU is necessary for LoRA (lots of quality degrade)
Full size grids are also shared for the followings: https://www.patreon.com/posts/112099700
Additionally, I have shared full training entire logs that you can see each checkpoint took time. I have shared best checkpoints, their step count and took time according to being either LoRA, Fine Tuning or Batch size 1 or 7 or 15 images or 256 images, so a very detailed article regarding completed.
Check the images to see all shared files in the post.
Furthermore, a very very detailed analysis having article written and all latest DreamBooth / Fine Tuning configs and LoRA configs are shared with Kohya GUI installers for both Windows, Runpod and Massed Compute.
Moreover, I have shared new 28 realism and 37 stylization testing prompts.
Current tutorials are as below:
Windows requirements CUDA, Python, cuDNN, and such : https://youtu.be/DrhUHnYfwC0
How to use SwarmUI : https://youtu.be/HKX8_F1Er_w
How to use FLUX on SwarmUI : https://youtu.be/bupRePUOA18
How to use Kohya GUI for FLUX training : https://youtu.be/nySGu12Y05k
How to use Kohya GUI for FLUX training on Cloud (RunPod and Massed Compute) : https://youtu.be/-uhL2nW7Ddw
Post
3875
Huge news for Kohya GUI - Now you can fully Fine Tune / DreamBooth FLUX Dev with as low as 6 GB GPUs without any quality loss compared to 48 GB GPUs - Moreover, Fine Tuning yields better results than any LoRA training could
Config Files
I published all configs here : https://www.patreon.com/posts/112099700
Tutorials
Fine tuning tutorial in production
Windows FLUX LoRA training (fine tuning is same just config changes) : https://youtu.be/nySGu12Y05k
Cloud FLUX LoRA training (RunPod and Massed Compute ultra cheap) : https://youtu.be/-uhL2nW7Ddw
LoRA Extraction
The checkpoint sizes are 23.8 GB but you can extract LoRA with almost no loss quality - I made a research and public article / guide for this as well
LoRA extraction guide from Fine Tuned checkpoint is here : https://www.patreon.com/posts/112335162
Info
This is just mind blowing. The recent improvements Kohya made for block swapping is just amazing.
Speeds are also amazing that you can see in image 2 - of course those values are based on my researched config and tested on RTX A6000 - same speed as almost RTX 3090
Also all trainings experiments are made at 1024x1024px. If you use lower resolution it will be lesser VRAM + faster speed
The VRAM usages would change according to your own configuration - likely speed as well
Moreover, Fine Tuning / DreamBooth yields better results than any LoRA could
Installers
1-Kohya GUI accurate branch and Windows Torch 2.5 Installers and test prompts shared here : https://www.patreon.com/posts/110879657
The link of Kohya GUI with accurate branch : https://github.com/bmaltais/kohya_ss/tree/sd3-flux.1
Config Files
I published all configs here : https://www.patreon.com/posts/112099700
Tutorials
Fine tuning tutorial in production
Windows FLUX LoRA training (fine tuning is same just config changes) : https://youtu.be/nySGu12Y05k
Cloud FLUX LoRA training (RunPod and Massed Compute ultra cheap) : https://youtu.be/-uhL2nW7Ddw
LoRA Extraction
The checkpoint sizes are 23.8 GB but you can extract LoRA with almost no loss quality - I made a research and public article / guide for this as well
LoRA extraction guide from Fine Tuned checkpoint is here : https://www.patreon.com/posts/112335162
Info
This is just mind blowing. The recent improvements Kohya made for block swapping is just amazing.
Speeds are also amazing that you can see in image 2 - of course those values are based on my researched config and tested on RTX A6000 - same speed as almost RTX 3090
Also all trainings experiments are made at 1024x1024px. If you use lower resolution it will be lesser VRAM + faster speed
The VRAM usages would change according to your own configuration - likely speed as well
Moreover, Fine Tuning / DreamBooth yields better results than any LoRA could
Installers
1-Kohya GUI accurate branch and Windows Torch 2.5 Installers and test prompts shared here : https://www.patreon.com/posts/110879657
The link of Kohya GUI with accurate branch : https://github.com/bmaltais/kohya_ss/tree/sd3-flux.1
models
66
MonsterMMORPG/Best_SD15_SDXL_Models
Updated
MonsterMMORPG/FLUX_Fine_Tuning_VS_LoRA_Final_Results
Updated
MonsterMMORPG/mich
Updated
MonsterMMORPG/Best_FLUX_Fine_Tunings_Comparisons
Updated
MonsterMMORPG/Big_FLUX_Fine_Tuning_Experiments
Updated
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1
MonsterMMORPG/256_Imgs_FLUX_Fine_Tuning_Trainings_Best
Updated
MonsterMMORPG/Generative-AI
Updated
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3
MonsterMMORPG/SECourses_SUPIR
Updated
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799
MonsterMMORPG/temp29
Updated
MonsterMMORPG/Patreon_SECourses_ROCKs
Updated