
# Paraphrase-Generation
​
## Model description
​
T5 Model for generating paraphrases of english sentences. Trained on the [Google PAWS](https://github.com/google-research-datasets/paws) dataset.
​
## How to use
​## Requires sentencepiece: # !pip install sentencepiece
PyTorch and TF models available
​
```python
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
​
tokenizer = AutoTokenizer.from_pretrained("Vamsi/T5_Paraphrase_Paws")  
model = AutoModelForSeq2SeqLM.from_pretrained("Vamsi/T5_Paraphrase_Paws").to('cuda')
​
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](https://github.com/Vamsi995/Paraphrase-Generator).

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


# Paraphrase-Generation
​
## Model description
​
T5 Model for generating paraphrases of english sentences. Trained on the Google PAWS dataset.
​
## How to use
​## Requires sentencepiece: # !pip install sentencepiece
PyTorch and TF models available
​


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

# Paraphrase-Generation
​ ## Model description
​
T5 Model for generating paraphrases of english sentences. Trained on the Google PAWS dataset.
​ ## How to use
​## Requires sentencepiece: # !pip install sentencepiece
PyTorch and TF models available
​


For more reference on training your own T5 model or using this model, do check out Paraphrase Generation.
TAGS
#transformers #pytorch #tf #jax #safetensors #t5 #text2text-generation #paraphrase-generation #text-generation #Conditional Generation #en #autotrain_compatible #has_space #text-generation-inference #region-us 
 # Paraphrase-Generation
​ ## Model description
​
T5 Model for generating paraphrases of english sentences. Trained on the Google PAWS dataset.
​ ## How to use
​## Requires sentencepiece: # !pip install sentencepiece
PyTorch and TF models available
​


For more reference on training your own T5 model or using this model, do check out Paraphrase Generation.
passage: TAGS
#transformers #pytorch #tf #jax #safetensors #t5 #text2text-generation #paraphrase-generation #text-generation #Conditional Generation #en #autotrain_compatible #has_space #text-generation-inference #region-us 
# Paraphrase-Generation
​## Model description
​
T5 Model for generating paraphrases of english sentences. Trained on the Google PAWS dataset.
​## How to use
​## Requires sentencepiece: # !pip install sentencepiece
PyTorch and TF models available
​


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