Update app.py

app.py

@@ -8,7 +8,7 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 dtype = torch.float16
 
 pipe = DiffusionPipeline.from_pretrained("Chan-Y/Chan-Y-Cyber-Stable-Realistic", 
-                                             torch_dtype=torch.float16).to(device)
+                                         torch_dtype=torch.float16).to(device)
 
 MAX_SEED = 999999999999999
 MAX_IMAGE_SIZE = 1344
@@ -21,13 +21,13 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
     generator = torch.Generator().manual_seed(seed)
     
     image = pipe(
-        prompt = prompt, 
-        negative_prompt = negative_prompt,
-        guidance_scale = guidance_scale, 
-        num_inference_steps = num_inference_steps, 
-        width = width, 
-        height = height,
-        generator = generator
+        prompt=prompt, 
+        negative_prompt=negative_prompt,
+        guidance_scale=guidance_scale, 
+        num_inference_steps=num_inference_steps, 
+        width=width, 
+        height=height,
+        generator=generator
     ).images[0] 
     
     return image, seed
@@ -36,19 +36,17 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
 examples = [
     ["Batman, cute modern Disney style, Pixar 3d portrait, ultra detailed, gorgeous, 3d zbrush, trending on dribbble, 8k render.",
      "",       
-     ,
+     12345,
      50]
 ]
 
-
-css="""
+css = """
 #col-container {
     margin: 0 auto;
     max-width: 580px;
 }
 """
 
-
 with gr.Blocks(css=css) as demo:
     
     with gr.Column(elem_id="col-container"):
@@ -58,83 +56,13 @@ with gr.Blocks(css=css) as demo:
         """)
         
         with gr.Row():
-            
-            prompt = gr.Text(
+            prompt = gr.Textbox(
                 label="Prompt",
                 show_label=False,
                 max_lines=1,
                 placeholder="Enter your prompt",
                 container=False,
             )
-            
             run_button = gr.Button("Run", scale=0)
         
-        result = gr.Image(label="Result", show_label=False)
-
-        with gr.Accordion("Advanced Settings", open=False):
-            
-            negative_prompt = gr.Text(
-                label="Negative prompt",
-                max_lines=1,
-                placeholder="Enter a negative prompt",
-            )
-            
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
-            
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-            
-            with gr.Row():
-                
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=64,
-                    value=1024,
-                )
-                
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=64,
-                    value=1024,
-                )
-            
-            with gr.Row():
-                
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=5.0,
-                )
-                
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=28,
-                )
-        
-    with gr.Accordion("Examples", open=False):
-        gr.Examples(
-            examples=examples,
-            inputs=[prompt, negative_prompt, seed, num_inference_steps]
-        )
-    gr.on(
-        triggers=[run_button.click, prompt.submit, negative_prompt.submit],
-        fn = infer,
-        inputs = [prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
-        outputs = [result, seed]
-    )
-    
-    demo.launch()
+        result = gr.Image(label="Result