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---
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language: "en"
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tags:
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- paraphrase-generation
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- text-generation
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- Conditional Generation
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inference: false
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---
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# Simple model for Paraphrase Generation
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## Model description
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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.
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## How to use
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```python
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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tokenizer = AutoTokenizer.from_pretrained("shrishail/t5_paraphrase_msrp_paws")
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model = AutoModelForSeq2SeqLM.from_pretrained("shrishail/t5_paraphrase_msrp_paws")
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sentence = "This is something which i cannot understand at all"
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text = "paraphrase: " + sentence + " </s>"
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encoding = tokenizer.encode_plus(text,pad_to_max_length=True, return_tensors="pt")
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input_ids, attention_masks = encoding["input_ids"].to("cuda"), encoding["attention_mask"].to("cuda")
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outputs = model.generate(
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input_ids=input_ids, attention_mask=attention_masks,
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max_length=256,
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do_sample=True,
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top_k=120,
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top_p=0.95,
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early_stopping=True,
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num_return_sequences=5
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)
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for output in outputs:
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line = tokenizer.decode(output, skip_special_tokens=True,clean_up_tokenization_spaces=True)
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print(line)
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```
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