Full Training Tutorial and Guide and Research For a FLUX Style
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Furkan Gözükara
MonsterMMORPG
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Check out my youtube page SECourses for Stable Diffusion tutorials. They will help you tremendously in every topic
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1 day ago
woah, some of these demo images look actually gud... i kinda lost hope for image diffusers there for a minute, but this is impressive. the one with the leaves cought me offguard.
And on such smol GPUs now too? that is super cool!
yep i hope it gets better with newer updates
reacted to
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post with 🤯🤝👍🧠➕😎🤗❤️👀🚀🔥
2 days ago
Post
4215
It is now possible to generate 16 Megapixel (4096x4096) raw images with SANA 4K model using under 8GB VRAM, 4 Megapixel (2048x2048) images using under 6GB VRAM, and 1 Megapixel (1024x1024) images using under 4GB VRAM thanks to new optimizations
13 January 2024 Update
Installers : https://www.patreon.com/posts/from-nvidia-labs-116474081
New 4K Tutorial Video : https://youtu.be/GjENQfHF4W8
Now the APP will use Diffusers Pipeline and it has huge VRAM optimizations
You need to reinstall
The models will be downloaded into your Hugging Face cache folder when you first time generate something
How to Get Installation Logs and How to Change Hugging Face Cache Folder :
https://www.patreon.com/posts/108419878
Please make a fresh install
When you enable all 4 optimizations the VRAM usages are like below
Make sure shared VRAM is enabled because initial loading of the model need more VRAM
Enable VAE Tiling + Enable VAE Slicing + Enable Model CPU Offload +
Enable Sequential CPU Offload
1K (1024x1024) : 4 GB GPUs
2K (2048x2048) : 6 GB GPUs
4K (4096x4096) : 8 GB GPUs
Still in any case may work on your GPU test it
Just Enable VAE Tiling + Enable Model CPU Offload works great in many cases
All below attached images are generated via SANA 4K model, they are RAW and their resolution is 5376x3072
Official repo page : https://github.com/NVlabs/Sana
13 January 2024 Update
Installers : https://www.patreon.com/posts/from-nvidia-labs-116474081
New 4K Tutorial Video : https://youtu.be/GjENQfHF4W8
Now the APP will use Diffusers Pipeline and it has huge VRAM optimizations
You need to reinstall
The models will be downloaded into your Hugging Face cache folder when you first time generate something
How to Get Installation Logs and How to Change Hugging Face Cache Folder :
https://www.patreon.com/posts/108419878
Please make a fresh install
When you enable all 4 optimizations the VRAM usages are like below
Make sure shared VRAM is enabled because initial loading of the model need more VRAM
Enable VAE Tiling + Enable VAE Slicing + Enable Model CPU Offload +
Enable Sequential CPU Offload
1K (1024x1024) : 4 GB GPUs
2K (2048x2048) : 6 GB GPUs
4K (4096x4096) : 8 GB GPUs
Still in any case may work on your GPU test it
Just Enable VAE Tiling + Enable Model CPU Offload works great in many cases
All below attached images are generated via SANA 4K model, they are RAW and their resolution is 5376x3072
Official repo page : https://github.com/NVlabs/Sana
-
- 2 replies
posted
an
update
2 days ago
Post
4215
It is now possible to generate 16 Megapixel (4096x4096) raw images with SANA 4K model using under 8GB VRAM, 4 Megapixel (2048x2048) images using under 6GB VRAM, and 1 Megapixel (1024x1024) images using under 4GB VRAM thanks to new optimizations
13 January 2024 Update
Installers : https://www.patreon.com/posts/from-nvidia-labs-116474081
New 4K Tutorial Video : https://youtu.be/GjENQfHF4W8
Now the APP will use Diffusers Pipeline and it has huge VRAM optimizations
You need to reinstall
The models will be downloaded into your Hugging Face cache folder when you first time generate something
How to Get Installation Logs and How to Change Hugging Face Cache Folder :
https://www.patreon.com/posts/108419878
Please make a fresh install
When you enable all 4 optimizations the VRAM usages are like below
Make sure shared VRAM is enabled because initial loading of the model need more VRAM
Enable VAE Tiling + Enable VAE Slicing + Enable Model CPU Offload +
Enable Sequential CPU Offload
1K (1024x1024) : 4 GB GPUs
2K (2048x2048) : 6 GB GPUs
4K (4096x4096) : 8 GB GPUs
Still in any case may work on your GPU test it
Just Enable VAE Tiling + Enable Model CPU Offload works great in many cases
All below attached images are generated via SANA 4K model, they are RAW and their resolution is 5376x3072
Official repo page : https://github.com/NVlabs/Sana
13 January 2024 Update
Installers : https://www.patreon.com/posts/from-nvidia-labs-116474081
New 4K Tutorial Video : https://youtu.be/GjENQfHF4W8
Now the APP will use Diffusers Pipeline and it has huge VRAM optimizations
You need to reinstall
The models will be downloaded into your Hugging Face cache folder when you first time generate something
How to Get Installation Logs and How to Change Hugging Face Cache Folder :
https://www.patreon.com/posts/108419878
Please make a fresh install
When you enable all 4 optimizations the VRAM usages are like below
Make sure shared VRAM is enabled because initial loading of the model need more VRAM
Enable VAE Tiling + Enable VAE Slicing + Enable Model CPU Offload +
Enable Sequential CPU Offload
1K (1024x1024) : 4 GB GPUs
2K (2048x2048) : 6 GB GPUs
4K (4096x4096) : 8 GB GPUs
Still in any case may work on your GPU test it
Just Enable VAE Tiling + Enable Model CPU Offload works great in many cases
All below attached images are generated via SANA 4K model, they are RAW and their resolution is 5376x3072
Official repo page : https://github.com/NVlabs/Sana
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-
- 2 replies
reacted to
their
post with 🤝🤯👍🧠➕😎🤗
6 days ago
Post
1717
Famous IC-Light - Relight Images - Advanced Gradio APP with Windows, RunPod, Massed Compute and Free Kaggle Account Installers Published
Installers are shared here : https://www.patreon.com/posts/famous-ic-light-119566071
1-Click to install and use on Windows, RunPod, Massed Compute and a free Kaggle account notebook
All working perfect with more advanced Gradio app than what was officially published on official repo : https://github.com/lllyasviel/IC-Light
Moreover,
Started another experimental product training for a client. Doing FLUX Dreambooth / Finetuning via Kohya SS GUI. GPU is L40S and batch size is 7. Config name : Batch_Size_7_48GB_GPU_46250MB_29.1_second_it_Tier_1.json
Full workflow, step by step tutorial and configs : https://youtu.be/FvpWy1x5etM
Check out the attached images in full resolution fore more info
Installers are shared here : https://www.patreon.com/posts/famous-ic-light-119566071
1-Click to install and use on Windows, RunPod, Massed Compute and a free Kaggle account notebook
All working perfect with more advanced Gradio app than what was officially published on official repo : https://github.com/lllyasviel/IC-Light
Moreover,
Started another experimental product training for a client. Doing FLUX Dreambooth / Finetuning via Kohya SS GUI. GPU is L40S and batch size is 7. Config name : Batch_Size_7_48GB_GPU_46250MB_29.1_second_it_Tier_1.json
Full workflow, step by step tutorial and configs : https://youtu.be/FvpWy1x5etM
Check out the attached images in full resolution fore more info