readme: A monolingual T5 model for Persian trained on OSCAR 21.09 (https://oscar-corpus.com/) corpus with self-supervised method. 35 Gig deduplicated version of Persian data was used for pre-training the model.
  
  It's similar to the English T5 model but just for Persian. You may need to fine-tune it on your specific task. 
  
  Example code:
  
  ```
  from transformers import T5ForConditionalGeneration,AutoTokenizer
  
  import torch
  
  model_name = "Ahmad/parsT5-base"
  tokenizer = AutoTokenizer.from_pretrained(model_name)
  model = T5ForConditionalGeneration.from_pretrained(model_name)
  
  input_ids = tokenizer.encode('دانش آموزان به <extra_id_0> میروند و <extra_id_1> میخوانند.', return_tensors='pt')
  with torch.no_grad():
      hypotheses = model.generate(input_ids)
  for h in hypotheses:
      print(tokenizer.decode(h))
  ```
  
  
  
  
  Steps: 725000
  
  Accuracy: 0.66
  
  Training More?
  ========
  
  To train the model further please refer to its github repository at:
  
  https://github.com/puraminy/parsT5
  