Update app.py

app.py

@@ -2,15 +2,14 @@ import gradio as gr
 from diffusers import StableDiffusionPipeline
 import torch
 
-# Load the Stable Diffusion model (use a lightweight version for Spaces)
+# Load the Stable Diffusion model (use CPU-compatible settings)
 model_id = "runwayml/stable-diffusion-v1-5"
-pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
-pipe = pipe.to("cuda")  # Use GPU if available
+pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float32)  # Use float32 for CPU
 
 # Function to generate image from description
 def generate_image(text_description):
-    # Generate image using Stable Diffusion
-    image = pipe(text_description, num_inference_steps=50, guidance_scale=7.5).images[0]
+    # Generate image using Stable Diffusion on CPU
+    image = pipe(text_description, num_inference_steps=25, guidance_scale=7.5).images[0]  # Reduced steps for speed
     
     # Optional: Add text to the image
     from PIL import Image, ImageDraw, ImageFont
@@ -28,7 +27,7 @@ def generate_image(text_description):
 # Gradio interface
 with gr.Blocks(title="Text-to-Image Generator") as demo:
     gr.Markdown("# Text-to-Image Generator")
-    gr.Markdown("Enter a description below and generate a detailed image!")
+    gr.Markdown("Enter a description below and generate a detailed image! (Note: Running on CPU may be slow)")
     
     with gr.Row():
         with gr.Column():