readme: ---
  language: en
  ---
  A simple question-generation model built based on SQuAD 2.0 dataset. 
  Example use: 
  
  ```python
  from transformers import T5Config, T5ForConditionalGeneration, T5Tokenizer
  
  model_name = "allenai/t5-small-squad2-question-generation"
  tokenizer = T5Tokenizer.from_pretrained(model_name)
  model = T5ForConditionalGeneration.from_pretrained(model_name)
  
  def run_model(input_string, **generator_args):
      input_ids = tokenizer.encode(input_string, return_tensors="pt")
      res = model.generate(input_ids, **generator_args)
      output = tokenizer.batch_decode(res, skip_special_tokens=True)
      print(output)
      return output
  
  
  run_model("shrouds herself in white and walks penitentially disguised as brotherly love through factories and parliaments; offers help, but desires power;")
  run_model("He thanked all fellow bloggers and organizations that showed support.")
  run_model("Races are held between April and December at the Veliefendi Hippodrome near Bakerky, 15 km (9 miles) west of Istanbul.")
  ```
  which should result in the following:
  ```
  ['What is the name of the man who is a brotherly love?']
  ['What did He thank all fellow bloggers and organizations that showed support?']
  ['Where is the Veliefendi Hippodrome located?']
  ``` 
  
  