amazonaws-la commited on
Commit
fabbd5e
1 Parent(s): 7014106

Update app.py

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Files changed (1) hide show
  1. app.py +2 -10
app.py CHANGED
@@ -10,9 +10,10 @@ import numpy as np
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  import PIL.Image
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  import spaces
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  import torch
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- import diffusers
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  from diffusers import AutoencoderKL, DiffusionPipeline, DDIMScheduler
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  DESCRIPTION = "# SDXL"
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  if not torch.cuda.is_available():
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  DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>"
@@ -27,15 +28,6 @@ ENABLE_USE_LORA = os.getenv("ENABLE_USE_LORA", "1") == "1"
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  ENABLE_USE_VAE = os.getenv("ENABLE_USE_VAE", "1") == "1"
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  device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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- schedulers = [
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- ("LMSDiscreteScheduler", diffusers.schedulers.scheduling_lms_discrete.LMSDiscreteScheduler),
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- ("DDIMScheduler", diffusers.schedulers.scheduling_ddim.DDIMScheduler),
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- ("DPMSolverMultistepScheduler", diffusers.schedulers.scheduling_dpmsolver_multistep.DPMSolverMultistepScheduler),
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- ("EulerDiscreteScheduler", diffusers.schedulers.scheduling_euler_discrete.EulerDiscreteScheduler),
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- ("PNDMScheduler", diffusers.schedulers.scheduling_pndm.PNDMScheduler),
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- ("DDPMScheduler", diffusers.schedulers.scheduling_ddpm.DDPMScheduler),
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- ("EulerAncestralDiscreteScheduler", diffusers.schedulers.scheduling_euler_ancestral_discrete.EulerAncestralDiscreteScheduler)
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- ]
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  models = ["cagliostrolab/animagine-xl-3.0"] # Substitua isso pelo valor real do modelo selecionado
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  def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
 
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  import PIL.Image
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  import spaces
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  import torch
 
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  from diffusers import AutoencoderKL, DiffusionPipeline, DDIMScheduler
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+ pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config)
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+
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  DESCRIPTION = "# SDXL"
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  if not torch.cuda.is_available():
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  DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>"
 
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  ENABLE_USE_VAE = os.getenv("ENABLE_USE_VAE", "1") == "1"
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  device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 
 
 
 
 
 
 
 
 
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  models = ["cagliostrolab/animagine-xl-3.0"] # Substitua isso pelo valor real do modelo selecionado
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  def randomize_seed_fn(seed: int, randomize_seed: bool) -> int: