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Friedrich Marty

Smorty100
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https://gitlab.com/users/Marty_Friedrich/projects

AI & ML interests

I'm most interested in content rerouting between LLM and VLLM agens for automation possibilities. Using templates for each agent which is then filled in by another agents inputs seems really useful.

Recent Activity

reacted to etemiz's post with 😎 about 10 hours ago
Updated the Hoopoe model which is taking faith related and religious texts in. https://huggingface.co/etemiz/Hoopoe-8B-Llama-3.1 Faith score went from 8% to 54%. Expect more updates and increase in the score. I also did the instruct fine tuning before adding faith to the model. So some of the improvements may be there because I started with llama 3.1 base and not the instruct. Here are some comparisons with original Llama 3.1:
reacted to etemiz's post with 👀 about 10 hours ago
Updated the Hoopoe model which is taking faith related and religious texts in. https://huggingface.co/etemiz/Hoopoe-8B-Llama-3.1 Faith score went from 8% to 54%. Expect more updates and increase in the score. I also did the instruct fine tuning before adding faith to the model. So some of the improvements may be there because I started with llama 3.1 base and not the instruct. Here are some comparisons with original Llama 3.1:
replied to MonsterMMORPG's post 7 days ago
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
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