Update app.py

app.py

@@ -7,7 +7,7 @@ import numpy as np
 pipeline = LatentDiffusionUncondPipeline.from_pretrained("CompVis/latent-diffusion-celeba-256")
 
 
-def predict(steps=1, seed):
+def predict(steps=1, seed=42):
     generator = torch.manual_seed(seed)
     image = pipeline(generator=generator, num_inference_steps=steps)["sample"]
     image_processed = image.cpu().permute(0, 2, 3, 1)