Shivam More
Shivam77
AI & ML interests
None yet
Recent Activity
Reacted to
MonsterMMORPG's
post
with 🔥
about 2 months ago
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
Organizations
models
None public yet
datasets
None public yet