transformers/model_cards/Vamsi/T5_Paraphrase_Paws

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

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Paraphrase-Generation

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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
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tokenizer = AutoTokenizer.from_pretrained("Vamsi/T5_Paraphrase_Paws")  
model = AutoModelForSeq2SeqLM.from_pretrained("Vamsi/T5_Paraphrase_Paws")
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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)
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For more reference on training your own T5 model or using this model, do check out Paraphrase Generation.