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Daniel Jarvis

JarvisLabs

AI & ML interests

AI, Datascience, IOT, Recyling and more

Recent Activity

updated a Space 2 months ago

ARC-NECT/FAW-AI-APP

reacted to MonsterMMORPG's post with 🔥 4 months ago

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

updated a model 5 months ago

JarvisLabs/SIOUX-flux

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JarvisLabs's activity

updated a Space 2 months ago

Flux Traning

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reacted to MonsterMMORPG's post with 🔥 4 months ago

Post

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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