Update app.py

app.py

@@ -112,14 +112,14 @@ def load_and_prepare_model(model_id):
     #vae = AutoencoderKL.from_pretrained('cross-attention/asymmetric-autoencoder-kl-x-2',use_safetensors=False)
     #vae = AutoencoderKL.from_single_file('https://huggingface.co/ford442/sdxl-vae-bf16/mySLR/myslrVAE_v10.safetensors')
     #vaeX = AutoencoderKL.from_pretrained("stabilityai/sd-vae-ft-mse",use_safetensors=True)
-    #vaeX = AutoencoderKL.from_pretrained('ford442/Juggernaut-XI-v11-fp32',subfolder='vae').to(torch.bfloat16)   #  ,use_safetensors=True  FAILS
+    vaeX = AutoencoderKL.from_pretrained('ford442/Juggernaut-XI-v11-fp32',subfolder='vae').to(torch.bfloat16)   #  ,use_safetensors=True  FAILS
     #vaeX = AutoencoderKL.from_pretrained('ford442/RealVisXL_V5.0_FP64',subfolder='vae').to(torch.bfloat16)   #  ,use_safetensors=True  FAILS
     #unetX = UNet2DConditionModel.from_pretrained('ford442/RealVisXL_V5.0_FP64',subfolder='unet').to(torch.bfloat16)   #  ,use_safetensors=True  FAILS
   #  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)
     #sched = EulerAncestralDiscreteScheduler.from_pretrained("SG161222/RealVisXL_V5.0", subfolder='scheduler',beta_schedule="scaled_linear", steps_offset=1,timestep_spacing="trailing"))
     #sched = EulerAncestralDiscreteScheduler.from_pretrained("SG161222/RealVisXL_V5.0", subfolder='scheduler', steps_offset=1,timestep_spacing="trailing")
     #sched = EulerAncestralDiscreteScheduler.from_pretrained('SG161222/RealVisXL_V5.0', subfolder='scheduler',beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1,use_karras_sigmas=True)
-    #sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear")
+    sched = EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear")
     #pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0").to(torch.bfloat16)
     #pipeX = StableDiffusionXLPipeline.from_pretrained("ford442/Juggernaut-XI-v11-fp32",use_safetensors=True)
     
@@ -135,16 +135,17 @@ def load_and_prepare_model(model_id):
      #  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),
      #   vae=AutoencoderKL.from_pretrained("stabilityai/sdxl-vae",repo_type='model',safety_checker=None, torch_dtype=torch.float32),
        # vae=AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16",repo_type='model',safety_checker=None),
-        #vae=vae,
+        vae=vaeX,
         #unet=pipeX.unet,
-        #scheduler = sched,
+        scheduler = sched,
       #  scheduler = EulerAncestralDiscreteScheduler.from_config(pipeX.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
         #scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset =1)
     )
     #pipe.unet=UNet2DConditionModel.from_pretrained('ford442/RealVisXL_V5.0_FP64',subfolder='unet').to(torch.bfloat16)
     #pipe.unet=UNet2DConditionModel.from_pretrained('SG161222/RealVisXL_V5.0',subfolder='unet').to(torch.bfloat16)
     #pipe.vae = AsymmetricAutoencoderKL.from_pretrained('cross-attention/asymmetric-autoencoder-kl-x-2').to(torch.bfloat16)   #  ,use_safetensors=True  FAILS
-    pipe.vae = AutoencoderKL.from_pretrained('ford442/Juggernaut-XI-v11-fp32',subfolder='vae').to(torch.bfloat16)   #  ,use_safetensors=True  FAILS
+    #pipe.vae = AutoencoderKL.from_pretrained('ford442/Juggernaut-XI-v11-fp32',subfolder='vae')   #  ,use_safetensors=True  FAILS
+    #pipe.vae.to(torch.bfloat16)  
     #sched = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear",use_karras_sigmas=True, algorithm_type="dpmsolver++")
     #pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
     #pipe.scheduler = DPMSolverMultistepScheduler.from_pretrained('SG161222/RealVisXL_V5.0', subfolder='scheduler', algorithm_type='sde-dpmsolver++')
@@ -159,7 +160,7 @@ def load_and_prepare_model(model_id):
     #pipe.vae=vae.to(torch.bfloat16)
     #pipe.unet=pipeX.unet
     #pipe.scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", beta_start=0.00085, beta_end=0.012, steps_offset=1)
-    pipe.scheduler=EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear")
+    #pipe.scheduler=EulerAncestralDiscreteScheduler.from_pretrained('ford442/RealVisXL_V5.0_BF16', subfolder='scheduler',beta_schedule="scaled_linear")
 
     pipe.to(device)
     pipe.to(torch.bfloat16)