How to run on GPU with 8GB memory.
I have a RTX 2080 (via TrainML), and I am trying to use stable-diffusion-xl-base-1.0, but every time CUDA runs out of memory only after loading the model. Apparently I only need 20 more MBs but even that is not available, is there any way I can only load parts that I need and not include any other tensors?
My use case is only txt2img.
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Maybe float16 or int8
adjust your virtual memory , i am using GT 1030 with 4 GB, and my system RAM is 16GB , i adjust my Vram now my GPU is 11GB , STXL 1.0 is working fine for me. but in slow motion .
adjust your virtual memory , i am using GT 1030 with 4 GB, and my system RAM is 16GB , i adjust my Vram now my GPU is 11GB , STXL 1.0 is working fine for me. but in slow motion .
how to adjust my server's virtual ram, then add it to GPU ram
Same question, I am using a linux machine for my training and I can find (on internet) adjusting RAM for windows machine, but do you have any idea for linux or for cloud services?
just buy it.