File size: 1,361 Bytes
7b81ced
 
 
 
 
 
 
 
 
02bc3ad
 
 
 
d4e79cc
02bc3ad
 
 
 
 
d4e79cc
 
 
02bc3ad
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
---

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


# 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)

​

```