metadata

language: en
tags:
  - paraphrase-generation
  - text-generation
  - Conditional Generation
inference: false

Paraphrase-Generation

Model description

T5 Model for generating paraphrases of english sentences. Trained on the Google PAWS dataset.

How to use

PyTorch and TF models available

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("Vamsi/T5_Paraphrase_Paws")  
model = AutoModelForSeq2SeqLM.from_pretrained("Vamsi/T5_Paraphrase_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)

For more reference on training your own T5 model or using this model, do check out Paraphrase Generation.