readme: ---
  language: "en"
  tags:
  - paraphrase-generation
  - text-generation
  - Conditional Generation
  inference: false
  ---
  
  # Simple model for Paraphrase Generation
  ​
  ## Model description
  ​
  T5-based model for generating paraphrased sentences. It is trained on the labeled [MSRP](https://www.microsoft.com/en-us/download/details.aspx?id=52398) and [Google PAWS](https://github.com/google-research-datasets/paws) dataset.
  ​
  ## How to use
  ​
  ```python
  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
  
  tokenizer = AutoTokenizer.from_pretrained("shrishail/t5_paraphrase_msrp_paws")
  model = AutoModelForSeq2SeqLM.from_pretrained("shrishail/t5_paraphrase_msrp_paws")
  ​
  sentence = "This is something which i cannot understand at all"
  text =  "paraphrase: " + sentence + " </s>"
  encoding = tokenizer.encode_plus(text,pad_to_max_length=True, return_tensors="pt")
  input_ids, attention_masks = encoding["input_ids"].to("cuda"), encoding["attention_mask"].to("cuda")
  outputs = model.generate(
      input_ids=input_ids, attention_mask=attention_masks,
      max_length=256,
      do_sample=True,
      top_k=120,
      top_p=0.95,
      early_stopping=True,
      num_return_sequences=5
  )
  for output in outputs:
      line = tokenizer.decode(output, skip_special_tokens=True,clean_up_tokenization_spaces=True)
      print(line)
  ​
  ```
  
  