Update app.py

app.py

@@ -3,7 +3,7 @@ import torch
 from diffusers import StableDiffusionPipeline
 import gradio as gr
 
-# Use a smaller Stable Diffusion model for CPU
+# Load a lighter model for CPU
 model_id = "stabilityai/stable-diffusion-2-1-base"
 
 pipe = StableDiffusionPipeline.from_pretrained(
@@ -11,25 +11,23 @@ pipe = StableDiffusionPipeline.from_pretrained(
     torch_dtype=torch.float32
 ).to("cpu")
 
-# Optimize for CPU
+# CPU-friendly optimization
 pipe.enable_attention_slicing()
-pipe.enable_sequential_cpu_offload()
 
 def generate(prompt):
-    # Keep steps and resolution low for faster generation
     image = pipe(
         prompt,
-        num_inference_steps=12,  # lower steps = faster
+        num_inference_steps=12,   # keep low for speed
         guidance_scale=7,        # balanced CFG
-        width=384,               # lower res (CPU safe)
+        width=384,               # smaller resolution
         height=384
     ).images[0]
     return image
 
 with gr.Blocks(css=".gradio-container {max-width: 800px; margin: auto;}") as demo:
-    gr.Markdown("## 🎨 AI Image Generator (CPU Friendly)\nType your prompt and get results in ~20s (CPU).")
+    gr.Markdown("## 🎨 AI Image Generator (CPU)\nType your prompt and generate in ~20s.")
 
-    prompt = gr.Textbox(label="Prompt", placeholder="A castle on a hill at sunset")
+    prompt = gr.Textbox(label="Prompt", placeholder="A futuristic city at night")
     output = gr.Image(type="pil", label="Generated Image")
     btn = gr.Button("🚀 Generate")