Update app.py

app.py

@@ -11,14 +11,14 @@ tqdm.monitor_interval = 0
 
 # Load the diffusion pipelines
 pipe1 = StableDiffusionXLPipeline.from_pretrained(
-    "kayfahaarukku/UrangDiffusion-1.0", 
+    "kayfahaarukku/UrangDiffusion-1.1", 
     torch_dtype=torch.float16, 
     custom_pipeline="lpw_stable_diffusion_xl",
 )
 pipe1.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe1.scheduler.config)
 
 pipe2 = StableDiffusionXLPipeline.from_pretrained(
-    "kayfahaarukku/UrangDiffusion-1.1", 
+    "kayfahaarukku/UrangDiffusion-1.2", 
     torch_dtype=torch.float16, 
     custom_pipeline="lpw_stable_diffusion_xl",
 )
@@ -43,7 +43,7 @@ def generate_comparison(prompt, negative_prompt, use_defaults, resolution, guida
     
     width, height = map(int, resolution.split('x'))
     
-    # Generate image with UrangDiffusion-1.0
+    # Generate image with UrangDiffusion-1.1
     image1 = pipe1(
         prompt, 
         negative_prompt=negative_prompt,
@@ -56,7 +56,7 @@ def generate_comparison(prompt, negative_prompt, use_defaults, resolution, guida
         callback_steps=1
     ).images[0]
 
-    # Generate image with model-x
+    # Generate image with UrangDiffusion-1.2
     image2 = pipe2(
         prompt, 
         negative_prompt=negative_prompt,
@@ -85,8 +85,8 @@ def reset_inputs():
 
 with gr.Blocks(title="UrangDiffusion Comparison Demo", theme="NoCrypt/miku@1.2.1") as demo:
     gr.HTML(
-        "<h1>UrangDiffusion 1.0 vs 1.1 Comparison Demo</h1>"
-        "This demo showcases a comparison between UrangDiffusion 1.0 and 1.1."
+        "<h1>UrangDiffusion 1.1 vs 1.2 Comparison Demo</h1>"
+        "This demo showcases a comparison between UrangDiffusion 1.1 and 1.2."
         )
     with gr.Row():
         with gr.Column():
@@ -110,8 +110,8 @@ with gr.Blocks(title="UrangDiffusion Comparison Demo", theme="NoCrypt/miku@1.2.1
 
         with gr.Column():
             with gr.Row():
-                output_image1 = gr.Image(type="pil", label="UrangDiffusion 1.0")
-                output_image2 = gr.Image(type="pil", label="UrangDiffusion 1.1")
+                output_image1 = gr.Image(type="pil", label="UrangDiffusion 1.1")
+                output_image2 = gr.Image(type="pil", label="UrangDiffusion 1.2")
             with gr.Accordion("Parameters", open=False):
                 gr.Markdown(
                     """