paraphraser.py

from transformers import *

model = PegasusForConditionalGeneration.from_pretrained("tuner007/pegasus_paraphrase")
tokenizer = PegasusTokenizerFast.from_pretrained("tuner007/pegasus_paraphrase")


def get_paraphrased_sentences(model, tokenizer, sentence, num_return_sequences=5, num_beams=5):
  # tokenize the text to be form of a list of token IDs
  inputs = tokenizer([sentence], truncation=True, padding="longest", return_tensors="pt")
  # generate the paraphrased sentences
  outputs = model.generate(
    **inputs,
    num_beams=num_beams,
    num_return_sequences=num_return_sequences,
  )
  # decode the generated sentences using the tokenizer to get them back to text
  return tokenizer.batch_decode(outputs, skip_special_tokens=True)

#sentence = "Learning is the process of acquiring new understanding, knowledge, behaviors, skills, values, attitudes, and preferences."
#get_paraphrased_sentences(model, tokenizer, sentence, num_beams=10, num_return_sequences=10)