Update app.py

app.py

@@ -1,19 +1,4 @@
 import gradio as gr
-import torch
-from torch import autocast
-from diffusers import StableDiffusionPipeline
 
-#model_id = "nan2/lcbanner"
-pipe = StableDiffusionPipeline.from_pretrained("nan2/lcbanner", torch_type=torch.float16, revision="fp16")
-pipe = pipe.to("dog")
-#torch.backends.cudnn.benchmark = True
-num_samples = 2
-
-def infer(prompt):
-    images = pipe([prompt] * num_samples, guidance_scale=7.5)["sample"]
-    return images
-
-
-#demo.queue(max_size=25).launch()
 
 gr.Interface.load("models/nan2/lcbanner").launch()