content.raw: Kohya brought massive improvements to FLUX LoRA (as low as 4 GB GPUs) and DreamBooth / Fine-Tuning (as low as 6 GB GPUs) training - check attached images in full size to see full details
content.type: text
content.value: Kohya brought massive improvements to FLUX LoRA (as low as 4 GB GPUs) and DreamBooth / Fine-Tuning (as low as 6 GB GPUs) training - check attached images in full size to see full details
content.type: new_line
content.type: new_line
content.raw: You can download all configs and full instructions
content.type: text
content.value: You can download all configs and full instructions
content.type: new_line
content.type: new_line
content.raw: > 
content.type: text
content.value: > 
content.href: https://www.patreon.com/posts/112099700
content.raw: https://www.patreon.com/posts/112099700
content.type: link
content.raw:  - Fine Tuning post
content.type: text
content.value:  - Fine Tuning post
content.type: new_line
content.type: new_line
content.raw: > 
content.type: text
content.value: > 
content.href: https://www.patreon.com/posts/110879657
content.raw: https://www.patreon.com/posts/110879657
content.type: link
content.raw:  - LoRA post
content.type: text
content.value:  - LoRA post
content.type: new_line
content.type: new_line
content.raw: Kohya brought massive improvements to FLUX LoRA and DreamBooth / Fine-Tuning (min 6GB GPU) training.
content.type: text
content.value: Kohya brought massive improvements to FLUX LoRA and DreamBooth / Fine-Tuning (min 6GB GPU) training.
content.type: new_line
content.type: new_line
content.raw: Now as low as 4GB GPUs can train FLUX LoRA with decent quality and 24GB and below GPUs got a huge speed boost when doing Full DreamBooth / Fine-Tuning training
content.type: text
content.value: Now as low as 4GB GPUs can train FLUX LoRA with decent quality and 24GB and below GPUs got a huge speed boost when doing Full DreamBooth / Fine-Tuning training
content.type: new_line
content.type: new_line
content.raw: You need minimum 4GB GPU to do a FLUX LoRA training and minimum 6 GB GPU to do FLUX DreamBooth / Full Fine-Tuning training. It is just mind blowing.
content.type: text
content.value: You need minimum 4GB GPU to do a FLUX LoRA training and minimum 6 GB GPU to do FLUX DreamBooth / Full Fine-Tuning training. It is just mind blowing.
content.type: new_line
content.type: new_line
content.raw: You can download all configs and full instructions > 
content.type: text
content.value: You can download all configs and full instructions > 
content.href: https://www.patreon.com/posts/112099700
content.raw: https://www.patreon.com/posts/112099700
content.type: link
content.type: new_line
content.type: new_line
content.raw: The above post also has 1-click installers and downloaders for Windows, RunPod and Massed Compute
content.type: text
content.value: The above post also has 1-click installers and downloaders for Windows, RunPod and Massed Compute
content.type: new_line
content.type: new_line
content.raw: The model downloader scripts also updated and downloading 30+GB models takes total 1 minute on Massed Compute
content.type: text
content.value: The model downloader scripts also updated and downloading 30+GB models takes total 1 minute on Massed Compute
content.type: new_line
content.type: new_line
content.raw: You can read the recent updates here : 
content.type: text
content.value: You can read the recent updates here : 
content.href: https://github.com/kohya-ss/sd-scripts/tree/sd3?tab=readme-ov-file#recent-updates
content.raw: https://github.com/kohya-ss/sd-scripts/tree/sd3?tab=readme-ov-file#recent-updates
content.type: link
content.type: new_line
content.type: new_line
content.raw: This is the Kohya GUI branch : 
content.type: text
content.value: This is the Kohya GUI branch : 
content.href: https://github.com/bmaltais/kohya_ss/tree/sd3-flux.1
content.raw: https://github.com/bmaltais/kohya_ss/tree/sd3-flux.1
content.type: link
content.type: new_line
content.type: new_line
content.raw: Key thing to reduce VRAM usage is using block swap
content.type: text
content.value: Key thing to reduce VRAM usage is using block swap
content.type: new_line
content.type: new_line
content.raw: Kohya implemented the logic of OneTrainer to improve block swapping speed significantly and now it is supported for LoRAs as well
content.type: text
content.value: Kohya implemented the logic of OneTrainer to improve block swapping speed significantly and now it is supported for LoRAs as well
content.type: new_line
content.type: new_line
content.raw: Now you can do FP16 training with LoRAs on 24 GB and below GPUs
content.type: text
content.value: Now you can do FP16 training with LoRAs on 24 GB and below GPUs
content.type: new_line
content.type: new_line
content.raw: Now you can train a FLUX LoRA on a 4 GB GPU - key is FP8, block swap and using certain layers training (remember single layer LoRA training)
content.type: text
content.value: Now you can train a FLUX LoRA on a 4 GB GPU - key is FP8, block swap and using certain layers training (remember single layer LoRA training)
content.type: new_line
content.type: new_line
content.raw: It took me more than 1 day to test all newer configs, their VRAM demands, their relative step speeds and prepare the configs :)
content.type: text
content.value: It took me more than 1 day to test all newer configs, their VRAM demands, their relative step speeds and prepare the configs :)
rawContent: Kohya brought massive improvements to FLUX LoRA (as low as 4 GB GPUs) and DreamBooth / Fine-Tuning (as low as 6 GB GPUs) training - check attached images in full size to see full details
  
  You can download all configs and full instructions
  
  > https://www.patreon.com/posts/112099700 - Fine Tuning post
  
  > https://www.patreon.com/posts/110879657 - LoRA post
  
  Kohya brought massive improvements to FLUX LoRA and DreamBooth / Fine-Tuning (min 6GB GPU) training.
  
  Now as low as 4GB GPUs can train FLUX LoRA with decent quality and 24GB and below GPUs got a huge speed boost when doing Full DreamBooth / Fine-Tuning training
  
  You need minimum 4GB GPU to do a FLUX LoRA training and minimum 6 GB GPU to do FLUX DreamBooth / Full Fine-Tuning training. It is just mind blowing.
  
  You can download all configs and full instructions > https://www.patreon.com/posts/112099700
  
  The above post also has 1-click installers and downloaders for Windows, RunPod and Massed Compute
  
  The model downloader scripts also updated and downloading 30+GB models takes total 1 minute on Massed Compute
  
  You can read the recent updates here : https://github.com/kohya-ss/sd-scripts/tree/sd3?tab=readme-ov-file#recent-updates
  
  This is the Kohya GUI branch : https://github.com/bmaltais/kohya_ss/tree/sd3-flux.1
  
  Key thing to reduce VRAM usage is using block swap
  
  Kohya implemented the logic of OneTrainer to improve block swapping speed significantly and now it is supported for LoRAs as well
  
  Now you can do FP16 training with LoRAs on 24 GB and below GPUs
  
  Now you can train a FLUX LoRA on a 4 GB GPU - key is FP8, block swap and using certain layers training (remember single layer LoRA training)
  
  It took me more than 1 day to test all newer configs, their VRAM demands, their relative step speeds and prepare the configs :)
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