Update app.py

app.py

@@ -2,16 +2,14 @@ import gradio as gr
 from diffusers import StableDiffusionPipeline
 import torch
 
-# Load Stable Diffusion model (optimized for low-memory GPUs)
+# Load model without specifying fp16 revision
 model_id = "runwayml/stable-diffusion-v1-5"
 pipe = StableDiffusionPipeline.from_pretrained(
     model_id,
-    torch_dtype=torch.float16,
-    revision="fp16"  # Uses less VRAM
+    torch_dtype=torch.float16  # Still use fp16 precision
 ).to("cuda")
 
 def generate_image(prompt, negative_prompt="", steps=30, guidance_scale=7.5):
-    """Generate an image from text with customizable settings."""
     image = pipe(
         prompt,
         negative_prompt=negative_prompt,
@@ -20,23 +18,18 @@ def generate_image(prompt, negative_prompt="", steps=30, guidance_scale=7.5):
     ).images[0]
     return image
 
-# Gradio UI
-with gr.Blocks(title="RimageGen - Text-to-Image AI") as demo:
-    gr.Markdown("## 🚀 Generate Images from Text")
+with gr.Blocks(title="RimageGen") as demo:
+    gr.Markdown("## 🎨 Text-to-Image Generator")
     with gr.Row():
         with gr.Column():
-            prompt = gr.Textbox(label="Describe your image", placeholder="A cyberpunk cat wearing sunglasses")
-            negative_prompt = gr.Textbox(label="Exclude from image (optional)", placeholder="blurry, deformed, ugly")
-            steps = gr.Slider(1, 50, value=30, label="Inference Steps")
+            prompt = gr.Textbox(label="Prompt", placeholder="A cute corgi wearing a crown")
+            negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="blurry, deformed")
+            steps = gr.Slider(1, 50, value=30, label="Steps")
             guidance = gr.Slider(1, 15, value=7.5, label="Guidance Scale")
             submit = gr.Button("Generate")
         with gr.Column():
-            output = gr.Image(label="Generated Image")
+            output = gr.Image(label="Result")
 
-    submit.click(
-        generate_image,
-        inputs=[prompt, negative_prompt, steps, guidance],
-        outputs=output
-    )
+    submit.click(generate_image, inputs=[prompt, negative_prompt, steps, guidance], outputs=output)
 
-demo.launch(debug=True)
+demo.launch()