ford442 commited on
Commit
a0d4129
·
1 Parent(s): 25101ab

Update app.py

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Files changed (1) hide show
  1. app.py +3 -2
app.py CHANGED
@@ -117,16 +117,17 @@ def load_and_prepare_model(model_id):
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  add_watermarker=False,
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  use_safetensors=True,
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  # vae=AutoencoderKL.from_pretrained("BeastHF/MyBack_SDXL_Juggernaut_XL_VAE/MyBack_SDXL_Juggernaut_XL_VAE_V10(version_X).safetensors",repo_type='model',safety_checker=None),
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- vae=AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",repo_type='model',safety_checker=None).to(torch.bfloat16),
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  #scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset =1)
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  )
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  pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
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  #pipe.to('cuda')
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  # pipe.scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
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- pipe.unet = pipeX.unet.to(torch.bfloat16)
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  #pipe.to(dtype=torch.bfloat16)
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  pipe.to(device)
 
 
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  #pipe.to(torch.bfloat16)
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  #pipe.to(device, torch.bfloat16)
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  del pipeX
 
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  add_watermarker=False,
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  use_safetensors=True,
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  # vae=AutoencoderKL.from_pretrained("BeastHF/MyBack_SDXL_Juggernaut_XL_VAE/MyBack_SDXL_Juggernaut_XL_VAE_V10(version_X).safetensors",repo_type='model',safety_checker=None),
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+ vae=AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",torch_dtype=torch.float32,repo_type='model',safety_checker=None).to(torch.bfloat16),
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  #scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset =1)
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  )
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  pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
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  #pipe.to('cuda')
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  # pipe.scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
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  #pipe.to(dtype=torch.bfloat16)
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  pipe.to(device)
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+ pipe.unet = pipeX.unet.to(torch.bfloat16)
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+
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  #pipe.to(torch.bfloat16)
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  #pipe.to(device, torch.bfloat16)
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  del pipeX