Update app.py

app.py

@@ -18,7 +18,7 @@ dtype = torch.float16
 
 # AuraFlow model
 pipe = AuraFlowPipeline.from_pretrained(
-    "fal/AuraFlow",
+    "fal/AuraFlow-v0.2",
     torch_dtype=torch.float16
 ).to(device)
 
@@ -117,7 +117,7 @@ def generate_image(prompt, negative_prompt, seed, randomize_seed, width, height,
     
     return image, seed
 
-@spaces.GPU(duration=200)
+@spaces.GPU(duration=100)
 def process_workflow(image, text_prompt, vlm_model_choice, use_enhancer, model_choice, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps):
     if image is not None:
         # Convert image to PIL if it's not already