text: Title: Loading donut transformers model getting error
  Body: self.model = self.model.to(self.device)
  File “/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py”, line 1145, in to
  return self._apply(convert)
  File “/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py”, line 797, in _apply
  module._apply(fn)
  File “/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py”, line 797, in _apply
  module._apply(fn)
  File “/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py”, line 797, in _apply
  module._apply(fn)
  [Previous line repeated 1 more time]
  File “/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py”, line 820, in _apply
  param_applied = fn(param)
  File “/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py”, line 1143, in convert
  return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking)
  RuntimeError: CUDA error: device-side assert triggered
  Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.
  
  
   code:-
  class Donut:
      def __init__(self):
          try:
              self.processor = DonutProcessor.from_pretrained("naver-clova-ix/donut-base-finetuned-docvqa")
              self.model = VisionEncoderDecoderModel.from_pretrained("naver-clova-ix/donut-base-finetuned-docvqa")
              self.device = "cuda" if torch.cuda.is_available() else "cpu"
              if torch.cuda.is_available():
                  try:
                      self.device = torch.device("cuda")
                      self.model = self.model.to(self.device)
                      torch.cuda.empty_cache()
                  except RuntimeError as e:
                      console_logger.warning(f"{str(e)}")
  
          except Exception as e:
              console_logger.error(f"Failed to initialize Donut: {str(e)}")
              raise
  
  
  
  Versions:-
  torch==2.0.1+cu118
  torchaudio==2.0.2+cu118
  torchvision==0.15.2+cu118
  transformers==4.24.0
  Nvidia Driver :- Driver Version: 550.144.03 CUDA Version: 12.4
  Docker image :-  nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04
  