Create README.md

README.md

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+This is a training of a public LoRA style (2 seperate training each on 4x A6000).
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+Experimenting captions vs non-captions. So we will see which yields best results for style training on FLUX.
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+Generated captions with multi-GPU batch Joycaption app.
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+I am showing 5 examples of what Joycaption generates on FLUX dev. Left images are the original style images from the dataset.
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+I used my multi-GPU Joycaption APP (used 8x A6000 for ultra fast captioning) : https://www.patreon.com/posts/110613301
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+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6345bd89fe134dfd7a0dba40/LTfUYHXCpcwzt3_us0R26.png)
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+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
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+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6345bd89fe134dfd7a0dba40/BleDJpEMrCMXXRTCPKJqb.png)
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+The no caption dataset uses only ohwx 3d render as caption
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+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
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+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6345bd89fe134dfd7a0dba40/jK75d8i1x5hAHSYSsJNBd.png)
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+Total step count is being 500 * 114 / 4 (4x GPU - batch size 1) = 14250
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+Taking 37 hours currently if I don't terminate early
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+Will save a checkpoint once every 25 epochs
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+Full Windows Kohya LoRA training tutorial : https://youtu.be/nySGu12Y05k
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+Full Cloud Kohya LoRA training tutorial (Massed Compute + RunPod) : https://youtu.be/-uhL2nW7Ddw
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+Hopefully will share trained LoRA on Hugging Face and CivitAI along with full dataset including captions.
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+I got permission to share dataset but can't be used commercially.
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+Also I will hopefully share full workflow in the CivitAI and Hugging Face LoRA pages.
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+So far 450 epochs completed
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