Update app.py

app.py

@@ -131,7 +131,7 @@ def txt_to_img(model_path, prompt, neg_prompt, guidance, steps, width, height, g
  if is_colab or current_model == custom_model:
  pipe = StableDiffusionPipeline.from_pretrained(current_model_path, torch_dtype=torch.float16, scheduler=scheduler, safety_checker=lambda images, clip_input: (images, False))
  else:
- pipe = StableDiffusionPipeline.from_pretrained(current_model_path, torch_dtype=torch.float16, scheduler=scheduler, safety_checker=lambda images, clip_input: (images, False))
+ pipe = StableDiffusionPipeline.from_pretrained(current_model_path, torch_dtype=torch.float16, scheduler=scheduler)
  # pipe = pipe.to("cpu")
  # pipe = current_model.pipe_t2i
 
@@ -165,7 +165,7 @@ def img_to_img(model_path, prompt, neg_prompt, img, strength, guidance, steps, w
  if is_colab or current_model == custom_model:
  pipe = StableDiffusionImg2ImgPipeline.from_pretrained(current_model_path, torch_dtype=torch.float16, scheduler=scheduler, safety_checker=lambda images, clip_input: (images, False))
  else:
- pipe = StableDiffusionImg2ImgPipeline.from_pretrained(current_model_path, torch_dtype=torch.float16, scheduler=scheduler, safety_checker=lambda images, clip_input: (images, False))
+ pipe = StableDiffusionImg2ImgPipeline.from_pretrained(current_model_path, torch_dtype=torch.float16, scheduler=scheduler)
  # pipe = pipe.to("cpu")
  # pipe = current_model.pipe_i2i