This is a version of paraphrase detector by DeepPavlov ([details in the documentation](http://docs.deeppavlov.ai/en/master/features/overview.html#ranking-model-docs)) ported to the `Transformers` format. 
All credit goes to the authors of DeepPavlov.

The model has been trained on the dataset from http://paraphraser.ru/. 

It classifies texts as paraphrases (class 1) or non-paraphrases (class 0).

```python
import torch
from transformers import AutoModelForSequenceClassification, BertTokenizer
model_name = 'cointegrated/rubert-base-cased-dp-paraphrase-detection'
model = AutoModelForSequenceClassification.from_pretrained(model_name).cuda()
tokenizer = BertTokenizer.from_pretrained(model_name)
text1 = 'Сегодня на улице хорошая погода'
text2 = 'Сегодня на улице отвратительная погода'
batch = tokenizer(text1, text2, return_tensors='pt').to(model.device)
with torch.inference_mode():
    proba = torch.softmax(model(**batch).logits, -1).cpu().numpy()
print(proba)
# [[0.44876656 0.5512334 ]]
```