
# Simple model for Paraphrase Generation
​
## Model description
​
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.
​
## How to use
​
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("shrishail/t5_paraphrase_msrp_paws")
model = AutoModelForSeq2SeqLM.from_pretrained("shrishail/t5_paraphrase_msrp_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)
​
```


{"language": "en", "tags": ["paraphrase-generation", "text-generation", "Conditional Generation"], "inference": false}
transformers pytorch t5 text2text-generation paraphrase-generation text-generation Conditional Generation en autotrain_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #paraphrase-generation #text-generation #Conditional Generation #en #autotrain_compatible #text-generation-inference #region-us 


# Simple model for Paraphrase Generation
​
## Model description
​
T5-based model for generating paraphrased sentences. It is trained on the labeled MSRP and Google PAWS dataset.
​
## How to use
​



# Simple model for Paraphrase Generation
​ ## Model description
​
T5-based model for generating paraphrased sentences. It is trained on the labeled MSRP and Google PAWS dataset.
​ ## How to use
​
TAGS
#transformers #pytorch #t5 #text2text-generation #paraphrase-generation #text-generation #Conditional Generation #en #autotrain_compatible #text-generation-inference #region-us 
 # Simple model for Paraphrase Generation
​ ## Model description
​
T5-based model for generating paraphrased sentences. It is trained on the labeled MSRP and Google PAWS dataset.
​ ## How to use
​
passage: TAGS
#transformers #pytorch #t5 #text2text-generation #paraphrase-generation #text-generation #Conditional Generation #en #autotrain_compatible #text-generation-inference #region-us 
# Simple model for Paraphrase Generation
​## Model description
​
T5-based model for generating paraphrased sentences. It is trained on the labeled MSRP and Google PAWS dataset.
​## How to use
​