Update app.py

app.py

@@ -2,25 +2,22 @@ import gradio as gr
 from diffusers import DiffusionPipeline
 import torch
 
-# Load the Shap-E pipeline (adjust the model path if needed)
+# Load the pipeline
 pipeline = DiffusionPipeline.from_pretrained("openai/shap-e", torch_dtype=torch.float16)
 pipeline = pipeline.to("cuda" if torch.cuda.is_available() else "cpu")
 
 def generate_image(prompt):
-    # Generate an image based on the prompt using the pipeline
+    # Generate image using the prompt
     output = pipeline(prompt)
     return output.images[0]
 
-# Gradio interface setup
-title = "Shap-E Model Demo"
-description = "Generate images from text prompts using the Shap-E diffusion model."
-
+# Set up Gradio interface
 interface = gr.Interface(
     fn=generate_image,
     inputs=gr.Textbox(label="Prompt"),
     outputs=gr.Image(label="Generated Image"),
-    title=title,
-    description=description,
+    title="Shap-E Image Generation",
+    description="Generate images from text prompts using the Shap-E diffusion model."
 )
 
 if __name__ == "__main__":