update app

app.py

@@ -25,12 +25,12 @@ image = pipeline(prompt, num_inference_steps=50).images[0]
 def infer(prompt, negative_prompt, guidance_scale=10, num_inference_steps=50):
     neg = negative_prompt if negative_prompt else None
     imgs = []
-    while len(imgs) != 2:
+    while len(imgs) != 4:
         next_prompt = pipeline(prompt, negative_prompt=neg, guidance_scale=guidance_scale, num_inference_steps=num_inference_steps, num_images_per_prompt=5)
         for img, is_neg in zip(next_prompt.images, next_prompt.nsfw_content_detected):
             if not is_neg:
                 imgs.append(img)
-            if len(imgs) == 2:
+            if len(imgs) == 4:
                 break
             
     return imgs
@@ -41,9 +41,9 @@ output = gr.Gallery(label="Outputs").style(grid=(1,2))
 title = "KerasCV Stable Diffusion Demo on images of Bored Apes."
 description = "This is a dreambooth model fine-tuned on images the NFT collection of the Bored Ape Yacht Club. To try it, input the concept with `drawbayc ape`."
 examples=[
-    ["A drawing of a drawbayc ape as a cowboy", "", 12, 50],
-    ["A drawing of a drawbayc ape as a clown", "", 12, 50],
-    ["A drawing of a drawbayc ape as a turtle", "", 12, 50],
+    ["A drawing of a drawbayc ape as a cowboy", "", 12, 75],
+    ["A drawing of a drawbayc ape as a clown", "", 12, 75],
+    ["A drawing of a drawbayc ape as a turtle", "", 12, 75],
 
 ]
 
@@ -52,8 +52,6 @@ base_14 = "https://huggingface.co/nielsgl/dreambooth-bored-ape/resolve/main/"
 model_card_1 = f"""
 # KerasCV Stable Diffusion in Diffusers 🧨🤗
 
-# KerasCV Stable Diffusion in Diffusers 🧨🤗
-
 DreamBooth model for the `drawbayc ape` concept trained by nielsgl on the `nielsgl/bayc-tiny` dataset, images from this [Kaggle dataset](https://www.kaggle.com/datasets/stanleyjzheng/bored-apes-yacht-club).
 It can be used by modifying the `instance_prompt`: **a drawing of drawbayc ape**