fallenshock commited on
Commit
801b180
1 Parent(s): 0f741dd

Update app.py

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Files changed (1) hide show
  1. app.py +5 -5
app.py CHANGED
@@ -20,8 +20,8 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
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  pipe_sd3 = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", torch_dtype=torch.float16, token=os.getenv('HF_ACCESS_TOK'))
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  pipe_flux = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.float16, token=os.getenv('HF_ACCESS_TOK'))
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- pipe_sd3.to(device)
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- pipe_flux.to(device)
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  # scheduler = pipe.scheduler
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  # pipe = pipe.to(device)
@@ -97,15 +97,15 @@ def FlowEditRun(
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  if model_type == 'FLUX':
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  # pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.float16, token=os.getenv('HF_ACCESS_TOK'))
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- pipe = pipe_flux
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  elif model_type == 'SD3':
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  # pipe = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", torch_dtype=torch.float16, token=os.getenv('HF_ACCESS_TOK'))
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- pipe = pipe_sd3
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  else:
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  raise NotImplementedError(f"Model type {model_type} not implemented")
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  scheduler = pipe.scheduler
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- pipe = pipe.to(device)
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  pipe_sd3 = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", torch_dtype=torch.float16, token=os.getenv('HF_ACCESS_TOK'))
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  pipe_flux = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.float16, token=os.getenv('HF_ACCESS_TOK'))
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+ # pipe_sd3.to(device)
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+ # pipe_flux.to(device)
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  # scheduler = pipe.scheduler
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  # pipe = pipe.to(device)
 
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  if model_type == 'FLUX':
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  # pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.float16, token=os.getenv('HF_ACCESS_TOK'))
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+ pipe = pipe_flux.to(device)
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  elif model_type == 'SD3':
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  # pipe = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3-medium-diffusers", torch_dtype=torch.float16, token=os.getenv('HF_ACCESS_TOK'))
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+ pipe = pipe_sd3.to(device)
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  else:
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  raise NotImplementedError(f"Model type {model_type} not implemented")
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  scheduler = pipe.scheduler
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+ # pipe = pipe.to(device)
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