readme: ---
  license: mit
  language: th
  datasets:
  - thaisum
  widget:
  - text: "some news with head line"
  ---
  
  
  # How to use
  ```python3
  from transformers import MT5Tokenizer, MT5ForConditionalGeneration
  
  tokenizer = MT5Tokenizer.from_pretrained('juierror/thai-news-summarization')
  model = MT5ForConditionalGeneration.from_pretrained('juierror/thai-news-summarization')
  
  text = "some news with head line"
  
  tokenized_text = tokenizer(text, truncation=True, padding=True, return_tensors='pt')
      
  source_ids = tokenized_text['input_ids'].to("cpu", dtype = torch.long)
  source_mask = tokenized_text['attention_mask'].to("cpu", dtype = torch.long)
      
  generated_ids = model.generate(
      input_ids = source_ids,
      attention_mask = source_mask, 
      max_length=512,
      num_beams=5,
      repetition_penalty=1, 
      length_penalty=1, 
      early_stopping=True,
      no_repeat_ngram_size=2
  )
  
  pred = tokenizer.decode(generated_ids[0], skip_special_tokens=True, clean_up_tokenization_spaces=True)
  ```