Update app.py

app.py

@@ -16,15 +16,14 @@ pipe = DiffusionPipeline.from_pretrained(
     scheduler = DDIMScheduler(beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", clip_sample=False, set_alpha_to_one=False)
 ).to(device)
 
-generator = torch.Generator("cuda").manual_seed(0)
+#generator = torch.Generator("cuda").manual_seed(0)
 
 def infer(prompt, init_image):
     res = pipe.train(
         prompt,
         init_image,
         guidance_scale=7.5,
-        num_inference_steps=50,
-        generator=generator)
+        num_inference_steps=50)
     
     res = pipe(alpha=1)