readme: ---
  license: cc-by-nc-3.0
  ---
  
  # T5-base model trained for text paraphrase 
  
  You can load this model by:
  ```python
  from transformers import T5ForConditionalGeneration,T5TokenizerFast
  
  model = T5ForConditionalGeneration.from_pretrained(model_name_or_path)
  tokenizer = T5TokenizerFast.from_pretrained(model_name_or_path)
  ```
  
  A prefix "paraphrase: " should be added in font of the input sequence, i.e.:
  ```python
  input_st = "paraphrase: " + text + " </s>"
  ```
  You can find our scripts for generation in our [project GitHub](https://github.com/chiyuzhang94/PTSM/tree/main/paraphrase_generate)
  Please find more training details in our paper:
  
  [Decay No More: A Persistent Twitter Dataset for Learning Social Meaning](https://arxiv.org/pdf/2204.04611.pdf)
  
  Accepted by 1st Workshop on Novel Evaluation Approaches for Text Classification Systems on Social Media @ ICWSM-2022
  
    ```
  @inproceedings{zhang2022decay,
     title={Decay No More: A Persistent Twitter Dataset for Learning Social Meaning},
     author={Zhang, Chiyu and Abdul-Mageed, Muhammad and Nagoudi, El Moatez Billah},
     booktitle ={Proceedings of 1st Workshop on Novel Evaluation Approaches for Text Classification Systems on Social Media (NEATCLasS)}, 
     year={2022},
     url = {https://arxiv.org/pdf/2204.04611.pdf},
     publisher = {{AAAI} Press}, 
  }
    ```