Update app.py

app.py

@@ -286,7 +286,7 @@ device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 #Compile
 if torch.cuda.is_available():
  pipe = StableDiffusionXLPipeline.from_pretrained(
- "SG161222/RealVisXL_V5.0", #(or) use --- SG161222/RealVisXL_V4.0 / SG161222/RealVisXL_V4.0_Lightning --- for better results.
+ "SG161222/RealVisXL_V5.0_Lightning", #(or) use --- SG161222/RealVisXL_V4.0 / SG161222/RealVisXL_V4.0_Lightning --- for better results.
  torch_dtype=torch.float16,
  use_safetensors=True,
  add_watermarker=False,
@@ -394,7 +394,7 @@ def generate(
  "width": width,
  "height": height,
  "guidance_scale": guidance_scale,
- "num_inference_steps": 20,
+ "num_inference_steps": 30,
  "generator": generator,
  "num_images_per_prompt": num_images,
  "use_resolution_binning": use_resolution_binning,
@@ -525,9 +525,9 @@ with gr.Blocks(css=css, theme="bethecloud/storj_theme") as demo:
  num_inference_steps = gr.Slider(
  label="Steps",
  minimum=10,
- maximum=30,
+ maximum=60,
  step=1,
- value=15,
+ value=30,
  )
  with gr.Row():
  num_images_per_prompt = gr.Slider(