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Omost patch 1 - for 8GB VRAM GPU - 1920x1080 #81

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@xhoxye xhoxye commented Jun 7, 2024

The inspiration came from here #27, but I couldn't run it, so I modified a version myself
#63

  1. Seed randomization via -1, max int32 2 ** 31 - 1
  2. Use the drop-down menu to select LLM Model and Image Diffusion Model, and the Image Diffusion Model list reads the Omost\models\checkpoints path
  3. Save the image to the outputs directory and format the image name
  4. Print the loaded model name, seed value, dialogue and image rendering time in cmd, and other information
  5. Load the .safetensors file using the fp16 type

QQ截图20240607103121
QQ截图20240607102606

My pc, windows 10, 2070s-8GB vram, 64G ram, CPU 5600X

@xhoxye
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xhoxye commented Jun 7, 2024

如果你在国内,也可以使用我的中文版本,https://github.com/xhoxye/Omost_CN

@ginto-sakata
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Can you explain what your patch doing? Will it work on 8Gb cards?

@xhoxye
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xhoxye commented Jun 7, 2024

@ginto-sakata
Yes, it works fine on my 2070S-8GB vram gpu
fp16
model_pipeline = StableDiffusionXLImg2ImgPipeline.from_single_file(model_path, torch_dtype=torch.float16, variant="fp16")

@xhoxye xhoxye changed the title Omost patch 1 Omost patch 1 - for 8GB VRAM GPU Jun 7, 2024
@xhoxye
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xhoxye commented Jun 8, 2024

1920x1080 no problem
2024-06-08_08-09-40_0_c046db05da8644e1a5f5ad4da5920930
2024-06-08_07-57-16_0_4d759587ba76489a8c0b7d838956d5be

@xhoxye xhoxye changed the title Omost patch 1 - for 8GB VRAM GPU Omost patch 1 - for 8GB VRAM GPU - 1920x1080 Jun 8, 2024
@qwyan
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qwyan commented Jun 8, 2024

你好,怎么联系呢?

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xhoxye commented Jun 8, 2024

@qwyan
有什么问题在这里问
有其他事情可以私信,或者到我的分支上问

@ping3839
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如果你在国内,也可以使用我的中文版本,https://github.com/xhoxye/Omost_CN

我在国外也一样用

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4 participants