change model

app.py

@@ -25,17 +25,10 @@ def get_image_gen_pipeline():
         try:
             device = "cuda" if torch.cuda.is_available() else "cpu"
             dtype = torch.bfloat16
-            # Load fast tokenizer for the image pipeline
-            # tokenizer = AutoTokenizer.from_pretrained(
-            #     "black-forest-labs/FLUX.1-schnell",
-            #     # "black-forest-labs/FLUX.1-dev",
-            #     use_fast=True
-            # )
             _image_gen_pipeline = DiffusionPipeline.from_pretrained(
-                "black-forest-labs/FLUX.1-schnell",
-                # "black-forest-labs/FLUX.1-dev",
+                # "black-forest-labs/FLUX.1-schnell",
+                "black-forest-labs/FLUX.1-dev",
                 torch_dtype=dtype,
-            #     tokenizer=tokenizer
             ).to(device)
         except Exception as e:
             print(f"Error loading image generation model: {e}")
@@ -143,9 +136,9 @@ def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, num_in
         return None, f"Error generating image: {str(e)}"
  
 examples = [
-    "a tiny astronaut hatching from an egg on the moon",
-    "a cat holding a sign that says hello world",
-    "an anime illustration of a wiener schnitzel",
+    "a backpack for kids, flower style",
+    "medieval flip flops",
+    "cat shaped cake mold",
 ]
 
 css="""
@@ -308,11 +301,7 @@ def create_interface():
                     )
             
             gr.Examples(
-                examples=[
-                    "a backpack for kids, flower style",
-                    "medieval flip flops",
-                    "cat shaped cake mold"
-                ],
+                examples=examples,
                 fn=refine_prompt,
                 inputs = [prompt],
                 outputs = [refined_prompt],