Update app.py

app.py

@@ -130,10 +130,10 @@ def load_and_prepare_model(model_id):
    # pipe.scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
     #pipe.to(dtype=torch.bfloat16)
     pipe.unet = pipeX.unet
+    pipe.scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
     pipe.to(device)
     pipe.unet.to(torch.bfloat16)
     pipe.vae.to(torch.bfloat16)
-    pipe.scheduler=EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
     #pipe.to(torch.bfloat16)
     #pipe.to(device, torch.bfloat16)
     del pipeX
@@ -216,11 +216,11 @@ def generate_30(
         f.write(f"Steps: {num_inference_steps} \n")
         f.write(f"Guidance Scale: {guidance_scale} \n")
         f.write(f"SPACE SETUP: \n")
-        f.write(f"Use Safetensors: no \n")
-        f.write(f"Use Model Dtype: no \n")
-        f.write(f"Model Scheduler: Euler_a custom \n")
-        f.write(f"Model VAE: stabilityai/sdxl-vae  \n")
-        f.write(f"Model UNET: stabilityai after cuda \n")
+        f.write(f"Use Safetensors: True \n")
+        f.write(f"Use Model Dtype: yes \n")
+        f.write(f"Model Scheduler: Euler_a custom before cuda \n")
+        f.write(f"Model VAE: stabilityai/sdxl-vae before cuda to bfloat after cuda \n")
+        f.write(f"Model UNET: stabilityai before cuda to bfloat after cuda \n")
     upload_to_ftp(filename) 
     for i in range(0, num_images, BATCH_SIZE):
         batch_options = options.copy()