readme: ## Overview
  This model is a finetuned version of [mt5-small](https://huggingface.co/google/mt5-small) for question paraphrasing task in Turkish. As a generator model, its capabilities are currently investigated and there is an ongoing effort to further improve it. You can raise an issue [in this GitHub repo](https://github.com/monatis/tqp) for any comments, suggestions or interesting findings when using this model.
  
  ## Usage
  You can generate 5 paraphrases for the input question with The simple code below.
  
  ```python
  from transformers import AutoTokenizer, T5ForConditionalGeneration
  model_name = "mys/mt5-small-turkish-question-paraphrasing"
  tokenizer = AutoTokenizer.from_pretrained(model_name)
  model = T5ForConditionalGeneration.from_pretrained(model_name)
  
  tokens = tokenizer.encode_plus("Yarın toplantı kaçta başlıyor?", return_tensors='pt')
  paraphrases = model.generate(tokens['input_ids'], max_length=128, num_return_sequences=5, num_beams=5)
  tokenizer.batch_decode(paraphrases, skip_special_tokens=True)
  ```
  
  And the output will be something like:
  ```shell
  ['Yarın toplantı ne zaman başlıyor?',
   'Yarın toplantı saat kaçta başlıyor?',
   'Yarın toplantı saat kaçta başlar?',
   'Yarın toplantı ne zaman başlayacak?',
   'Yarın toplantı ne zaman başlar?']
  ```
  
  ## Dataset
  I used [TQP dataset V0.1](https://github.com/monatis/tqp) that I've published just recently. This model should be taken as as a baseline model for TQP dataset. A cleaning and further improvements in the dataset and an elaborate hyperparameter tuning may boost the performance.
  
  ## Citation
  If you find the dataset or model useful for your research, [consider citation](https://zenodo.org/record/4719801#.YIbI45AzZPZ).