readme: ## EXAMPLE
  ```python
  import requests
  import torch
  from PIL import Image
  from transformers import (
      VisionEncoderDecoderModel, 
      ViTFeatureExtractor, 
      PreTrainedTokenizerFast,
  )
  
  # device setting
  device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
  
  # load feature extractor and tokenizer
  encoder_model_name_or_path = "ddobokki/vision-encoder-decoder-vit-gpt2-coco-ko"
  feature_extractor = ViTFeatureExtractor.from_pretrained(encoder_model_name_or_path)
  tokenizer = PreTrainedTokenizerFast.from_pretrained(encoder_model_name_or_path)
  
  # load model
  model = VisionEncoderDecoderModel.from_pretrained(encoder_model_name_or_path)
  model.to(device)
  
  # inference
  url = 'http://images.cocodataset.org/val2017/000000039769.jpg'
  with Image.open(requests.get(url, stream=True).raw) as img:
      pixel_values = feature_extractor(images=img, return_tensors="pt").pixel_values
  
  generated_ids = model.generate(pixel_values.to(device),num_beams=5)
  generated_text = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
  
  >> ['고양이 두마리가 담요 위에 누워 있다.']
  ```
  