Update app.py

app.py

@@ -1,4 +1,3 @@
-
 import gradio as gr
 from PIL import Image
 from diffusers import DiffusionPipeline
@@ -6,7 +5,7 @@ from diffusers import DiffusionPipeline
 # Load model and scheduler
 ldm = DiffusionPipeline.from_pretrained("CompVis/ldm-text2im-large-256")
 
-def generate_image(prompt, negative_prompt, width, height):
+def generate_image(prompt, negative_prompt="Low quality", width=512, height=512):
     # Run pipeline in inference (sample random noise and denoise)
     images = ldm([prompt], num_inference_steps=50, eta=0.3, guidance_scale=6, negative_prompts=[negative_prompt]).images
     # Resize image to desired width and height
@@ -25,7 +24,8 @@ iface = gr.Interface(
     title="Image Generation",
     description="Generate images based on prompts.",
     article="For more information, visit the documentation: [link](https://docs.gradio.app/)",
+    examples=[["A painting of a squirrel eating a burger", "Low quality", 512, 512]]
 )
 
 # Launch the interface
-iface.launch()
+iface.launch()