Update app.py

app.py

@@ -49,6 +49,7 @@ if SAFETY_CHECKER:
 # Function 
 @spaces.GPU(enable_queue=True)
 def generate_image(prompt, ckpt):
+    print(prompt, ckpt)
 
     checkpoint = checkpoints[ckpt][0]
     num_inference_steps = checkpoints[ckpt][1] 
@@ -74,17 +75,13 @@ def generate_image(prompt, ckpt):
 
 
 # Gradio Interface
-description = """
-This demo utilizes the SDXL-Lightning model by ByteDance, which is a lightning-fast text-to-image generative model capable of producing high-quality images in 4 steps.
-As a community effort, this demo was put together by AngryPenguin. Link to model: https://huggingface.co/ByteDance/SDXL-Lightning
-"""
 
 with gr.Blocks(css="style.css") as demo:
-    gr.HTML("<h1><center>Text-to-Image with SDXL-Lightning ⚡</center></h1>")
-    gr.Markdown(description)
+    gr.HTML("<h1><center>SDXL-Lightning ⚡</center></h1>")
+    gr.HTML("<p>Lightning-fast text-to-image generation</p><p><a href='https://huggingface.co/ByteDance/SDXL-Lightning'>https://huggingface.co/ByteDance/SDXL-Lightning</a></p>")
     with gr.Group():
         with gr.Row():
-            prompt = gr.Textbox(label='Enter you image prompt:', scale=8)
+            prompt = gr.Textbox(label='Enter you image prompt', scale=8)
             ckpt = gr.Dropdown(label='Select inference steps',choices=['1-Step', '2-Step', '4-Step', '8-Step'], value='4-Step', interactive=True)
             submit = gr.Button(scale=1, variant='primary')
     img = gr.Image(label='SDXL-Lightning Generated Image')