Update app.py

app.py

@@ -1,4 +1,3 @@
-import spaces
 import gradio as gr
 import numpy as np
 import random
@@ -25,9 +24,6 @@ pipeline = DiffusionPipeline.from_pretrained(
 )
 pipeline.load_lora_weights(lora_weights_path)
 
-# Comment out the line for sequential CPU offloading
-# pipeline.enable_sequential_cpu_offload()
-
 pipeline = pipeline.to(device)
 
 MAX_SEED = np.iinfo(np.int32).max
@@ -53,9 +49,9 @@ def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance
     return image
 
 examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-    "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
+    ["Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"],
+    ["An astronaut riding a green horse"],
+    ["A delicious ceviche cheesecake slice"],
 ]
 
 css = """
@@ -195,9 +191,8 @@ with gr.Blocks(css=css) as demo:
                     value=30,
                 )
         
-        for example in examples:
-            gr.Button(example).click(lambda e=example: prompt.set_value(e))
-    
+        gr.Examples(examples=examples, inputs=prompt)
+
     run_button.click(
         fn=infer,
         inputs=[prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],