Update app.py

app.py

@@ -113,7 +113,7 @@ def load_and_prepare_model(model_id):
     pipeX = StableDiffusionXLPipeline.from_pretrained("SG161222/RealVisXL_V5.0",use_safetensors=True)
     pipe = StableDiffusionXLPipeline.from_pretrained(
         model_id,
-        torch_dtype=torch.bfloat16,
+       # torch_dtype=torch.bfloat16,
        # add_watermarker=False,
         use_safetensors=True,
      #  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),
@@ -132,9 +132,9 @@ def load_and_prepare_model(model_id):
     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.to(device)
-    pipe.unet.to(torch.bfloat16)
-    pipe.vae.to(torch.bfloat16)
-    #pipe.to(torch.bfloat16)
+    #pipe.unet.to(torch.bfloat16)
+    #pipe.vae.to(torch.bfloat16)
+    pipe.to(torch.bfloat16)
     #pipe.to(device, torch.bfloat16)
     del pipeX
     #sched = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, beta_schedule="scaled_linear", algorithm_type="dpmsolver++")
@@ -458,14 +458,14 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
                 minimum=448,
                 maximum=MAX_IMAGE_SIZE,
                 step=64,
-                value=768,
+                value=1024,
             )
             height = gr.Slider(
                 label="Height",
                 minimum=448,
                 maximum=MAX_IMAGE_SIZE,
                 step=64,
-                value=768,
+                value=1024,
             )
         with gr.Row():
             guidance_scale = gr.Slider(
@@ -480,7 +480,7 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
                 minimum=10,
                 maximum=1000,
                 step=10,
-                value=250,
+                value=140,
             )
 
     gr.Examples(