This is a training of a public LoRA style (4 seperate training each on 4x A6000).
Experimenting captions vs non-captions. So we will see which yields best results for style training on FLUX.
Generated captions with multi-GPU batch Joycaption app.
I am showing 5 examples of what Joycaption generates on FLUX dev. Left images are the original style images from the dataset.
# I used my multi-GPU Joycaption APP (used 8x A6000 for ultra fast captioning)
# https://www.patreon.com/posts/110613301
# I used my Gradio batch caption editor to edit some words and add activation token as ohwx 3d render
# https://www.patreon.com/posts/108992085
The no caption dataset uses only ohwx 3d render as caption
# I am using my newest 4x_GPU_Rank_1_SLOW_Better_Quality.json on 4X A6000 GPU and train 500 epochs - 114 images
# https://www.patreon.com/posts/110879657
## Inconsistent Dataset Training
This is the first training I made with the below dataset
[Inconsistent-Training-Dataset-Images-Grid.jpg](https://huggingface.co/MonsterMMORPG/3D-Cartoon-Style-FLUX/resolve/main/Inconsistent-Training-Dataset-Images-Grid.jpg)
When you pay attention to the grid image above shared, you will see that the dataset is not consistent
It has total 114 images
This training total step count was 500 * 114 / 4 (4x GPU - batch size 1) = 14250
It took like 37 hours on 4x RTX A6000 GPU with slow config - faster config would take like half
There were 2 trainings made with this dataset. Epoch 500 checkpoints are named as below
SECourses_Style_Inconsistent_DATASET_NO_Captions.safetensors
SECourses_Style_Inconsistent_DATASET_With_Captions.safetensors
Their checkpoints are saved in below folders
Training-Checkpoints-NO-Captions
Training-Checkpoints-With-Captions
Its grid results are shared below
https://huggingface.co/MonsterMMORPG/3D-Cartoon-Style-FLUX/resolve/main/Inconsistent-Training-Dataset-Results-Grid-26100x23700px.jpg
When you pay attention to above image you will see that it has inconsistent results
1 : https://youtu.be/bupRePUOA18
### [**FLUX: The First Ever Open Source txt2img Model Truly Beats Midjourney & Others - FLUX is Awaited SD3**](https://youtu.be/bupRePUOA18)
[](https://youtu.be/bupRePUOA18)
2 : https://youtu.be/nySGu12Y05k
### [**FLUX LoRA Training Simplified: From Zero to Hero with Kohya SS GUI (8GB GPU, Windows) Tutorial Guide**](https://youtu.be/nySGu12Y05k)
[](https://youtu.be/nySGu12Y05k)
3 : https://youtu.be/-uhL2nW7Ddw
### [**Blazing Fast & Ultra Cheap FLUX LoRA Training on Massed Compute & RunPod Tutorial - No GPU Required!**](https://youtu.be/-uhL2nW7Ddw)
[](https://youtu.be/-uhL2nW7Ddw)
Hopefully will share trained LoRA on Hugging Face and CivitAI along with full dataset including captions.
I got permission to share dataset but can't be used commercially.
Also I will hopefully share full workflow in the CivitAI and Hugging Face LoRA pages.
So far 450 epochs completed
