readme: ---
  license: "mit"
  ---
  
  This model takes text as input and returns the top five paraphrased versions of the input text. The T5 model is fine-tuned using persuasive ad transcripts.
  
  Example usage:
  
  ```python
  import torch
  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
  
  tokenizer = AutoTokenizer.from_pretrained("paragon-analytics/t5_para")  
  model = AutoModelForSeq2SeqLM.from_pretrained("paragon-analytics/t5_para").to(device)
  
  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)
  ```
  