Update app.py

app.py

@@ -114,7 +114,7 @@ def load_and_prepare_model(model_id):
     #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/RealVisXL_V5.0_FP64',subfolder='vae').to(torch.bfloat16)   #  ,use_safetensors=True  FAILS
-    #unetX = UNet2DConditionModel.from_pretrained('ford442/RealVisXL_V5.0_BF16',subfolder='unet').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")
@@ -141,6 +141,7 @@ def load_and_prepare_model(model_id):
       #  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.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
     #sched = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear",use_karras_sigmas=True, algorithm_type="dpmsolver++")
@@ -160,7 +161,7 @@ def load_and_prepare_model(model_id):
     
     #apply_hidiffusion(pipe)
 
-    #pipe.unet.set_default_attn_processor()
+    pipe.unet.set_default_attn_processor()
     pipe.vae.set_default_attn_processor()
     
     print(f'Pipeline: ')
@@ -218,7 +219,7 @@ def uploadNote():
         f.write(f"Use Model Dtype: no \n")
         f.write(f"Model Scheduler: Euler_a custom before cuda \n")
         f.write(f"Model VAE: juggernaut to bfloat before cuda then attn_proc \n")
-        f.write(f"Model UNET: default ford442/RealVisXL_V5.0_BF16 \n")
+        f.write(f"Model UNET: default ford442/RealVisXL_V5.0_FP64 to bfloat before cuda then attn_proc \n")
         f.write(f"Model HiDiffusion OFF \n")
         f.write(f"Model do_resize OFF \n")
     upload_to_ftp(filename)