Update app.py

app.py

@@ -5,9 +5,9 @@ import gradio as gr
 device = "cuda" if torch.cuda.is_available() else "cpu"
 pipeline = DiffusionPipeline.from_pretrained("anusha-bhambore/live-eventful")
 pipeline = pipeline.to(device)
-def generate_image_interface(prompt, negative_prompt, gender, age, num_inference_steps=50, weight=640):
+def generate_image_interface(prompt, negative_prompt, num_inference_steps=50, weight=640):
   params = {'prompt': prompt, 'num_inference_steps': num_inference_steps, 'num_images_per_prompt':2, 'height':int(1.2*weight),
-            'weight': weight, 'negative_prompt': negative_prompt,'gender': gender, 'age': age }
+            'weight': weight, 'negative_prompt': negative_prompt}
 
   img = pipeline(**params).images
   return img[0],img[1]