ford442 commited on
Commit
bafcb42
·
1 Parent(s): 7ac18af

Update app.py

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Files changed (1) hide show
  1. app.py +3 -1
app.py CHANGED
@@ -111,6 +111,7 @@ def load_and_prepare_model(model_id):
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  vae = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",safety_checker=None)
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  # vae = AutoencoderKL.from_pretrained("BeastHF/MyBack_SDXL_Juggernaut_XL_VAE/MyBack_SDXL_Juggernaut_XL_VAE_V10(version_X).safetensors",safety_checker=None).to(torch.bfloat16)
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  # vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16", safety_checker=None).to('cuda')
 
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  #pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0",torch_dtype=torch.float32)
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  #pipeX = StableDiffusionXLPipeline.from_pretrained("ford442/Juggernaut-XI-v11-fp32",torch_dtype=torch.float32)
@@ -127,10 +128,11 @@ def load_and_prepare_model(model_id):
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  # vae=AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16",repo_type='model',safety_checker=None),
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  # vae=vae,
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  # unet=pipeX.unet,
 
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  # scheduler = EulerAncestralDiscreteScheduler.from_config(pipeX.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
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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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- sched = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear",use_karras_sigmas=True, algorithm_type="dpmsolver++")
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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 = sched
 
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  vae = AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",safety_checker=None)
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  # vae = AutoencoderKL.from_pretrained("BeastHF/MyBack_SDXL_Juggernaut_XL_VAE/MyBack_SDXL_Juggernaut_XL_VAE_V10(version_X).safetensors",safety_checker=None).to(torch.bfloat16)
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  # vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16", safety_checker=None).to('cuda')
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+ sched = EulerAncestralDiscreteScheduler.from_config('ford442/Juggernaut-XI-v11-fp32', beta_schedule="scaled_linear",use_karras_sigmas=True)
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  #pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0",torch_dtype=torch.float32)
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  #pipeX = StableDiffusionXLPipeline.from_pretrained("ford442/Juggernaut-XI-v11-fp32",torch_dtype=torch.float32)
 
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  # vae=AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16",repo_type='model',safety_checker=None),
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  # vae=vae,
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  # unet=pipeX.unet,
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+ scheduler = sched
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  # scheduler = EulerAncestralDiscreteScheduler.from_config(pipeX.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
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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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+ #sched = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear",use_karras_sigmas=True, algorithm_type="dpmsolver++")
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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 = sched