Update app.py

app.py

@@ -38,7 +38,7 @@ def infer(prompt,
           negative_prompt = "", 
           seed = 0, 
           randomize_seed = False, 
-          guidance_scale = 5.0, 
+          guidance_scale = 6.0, 
           num_inference_steps = 25
           ):
     if not isinstance(image, dict):
@@ -68,12 +68,12 @@ def infer(prompt,
 examples = [
     ["一只带着红色帽子的小猫咪，圆脸，大眼，极度可爱，高饱和度，立体，柔和的光线", 
      "image/1.png", "image/1_masked.png"],
-    ["This is a mouth-watering hot pot scene, with all kinds of delicious ingredients cooking in the boiling pot, emitting intoxicating heat and aroma. The fiery red peppers and bright chili oil are shining, with attractive and fascinating colors. The delicate thin-cut beef, refreshing tofu skin, enoki mushrooms with rich abalone sauce, and crisp vegetables in the pot are combined together to create a colorful visual presentation", 
+    ["这是一幅令人垂涎欲滴的火锅画面，各种美味的食材在翻滚的锅中煮着，散发出的热气和香气令人陶醉。火红的辣椒和鲜艳的辣椒油熠熠生辉，具有诱人的招人入胜之色彩。锅内肉质细腻的薄切牛肉、爽口的豆腐皮、鲍汁浓郁的金针菇、爽脆的蔬菜，融合在一起，营造出五彩斑斓的视觉呈现", 
      "image/2.png", "image/2_masked.png"],
     ["穿着美少女战士的衣服，一件类似于水手服风格的衣服，包括一个白色紧身上衣，前胸搭配一个大大的红色蝴蝶结。衣服的领子部分呈蓝色，并且有白色条纹。她还穿着一条蓝色百褶裙，超高清，辛烷渲染，高级质感，32k，高分辨率，最好的质量，超级细节，景深", 
-     "image/3.png", "image/3_mask.png"],
-    ["Wearing Iron Man's clothes, high-tech armor, the main colors are red and gold, and there are some silverdecorations. There is a light-up round reactor device on the chest, full of futuristic technology. Ultra-clear , high-quality, ultra-realistic, high-resolution, best quality, super details, depth of field", 
-     "image/4.png", "image/4_mask.png"],
+     "image/3.png", "image/3_masked.png"],
+    ["穿着钢铁侠的衣服，高科技盔甲，主要颜色为红色和金色，并且有一些银色装饰。胸前有一个亮起的圆形反应堆装置，充满了未来科技感。超清晰，高质量，超逼真，高分辨率，最好的质量，超级细节，景深", 
+     "image/4.png", "image/4_masked.png"],
 ]
 
 css="""
@@ -125,7 +125,7 @@ with gr.Blocks(css=css) as Kolors:
                         minimum=0.0,
                         maximum=10.0,
                         step=0.1,
-                        value=5.0,
+                        value=6.0,
                     )
                     num_inference_steps = gr.Slider(
                         label="Number of inference steps",