Update app.py

app.py

@@ -43,7 +43,7 @@ def generate(schedul, num):
         scheduler = DDIMScheduler.from_pretrained(pipeline_name)
     else:
         scheduler = PNDMScheduler.from_pretrained(pipeline_name)
-    scheduler.set_timesteps(num_inference_steps=20)
+    scheduler.set_timesteps(num_inference_steps=num)
     x = torch.randn(1, 4, 64, 64).to(device)
     # Minimal sampling loop
     for i, t in tqdm(enumerate(scheduler.timesteps)):