readme: ---
  language:
  - vi
  
  tags:
  - t5
  - seq2seq
  
  # Machine translation for vietnamese
  ## Model Description
  T5-vi-en-small is a transformer model for vietnamese machine translation designed using T5 architecture.
  ## Training data
  T5-vi-en-small was trained on 4M sentence pairs (english,vietnamese)
  ### How to use
  
  ```py
  from transformers import T5ForConditionalGeneration, T5Tokenizer
  import torch
  if torch.cuda.is_available():       
      device = torch.device("cuda")
  
      print('There are %d GPU(s) available.' % torch.cuda.device_count())
  
      print('We will use the GPU:', torch.cuda.get_device_name(0))
  else:
      print('No GPU available, using the CPU instead.')
      device = torch.device("cpu")
  
  model = T5ForConditionalGeneration.from_pretrained("NlpHUST/t5-vi-en-small")
  tokenizer = T5Tokenizer.from_pretrained("NlpHUST/t5-vi-en-small")
  model.to(device)
  
  src = "Indonesia phỏng đoán nguyên nhân tàu ngầm chở 53 người mất tích bí ẩn"
  tokenized_text = tokenizer.encode(src, return_tensors="pt").to(device)
  model.eval()
  summary_ids = model.generate(
                      tokenized_text,
                      max_length=256, 
                      num_beams=5,
                      repetition_penalty=2.5, 
                      length_penalty=1.0, 
                      early_stopping=True
                  )
  output = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
  print(output)
  
  Indonesia anticipates the cause of the submarine transporting 53 mysterious missing persons
  
  ```