Rut5 Base Paraphraser

🚀 Russian Sentence Paraphraser

This project offers a paraphraser specifically designed for Russian sentences. It effectively addresses the need for rephrasing Russian text, providing users with diverse ways to express the same meaning.

✨ Features

• Russian Language Focus: Tailored for paraphrasing Russian sentences.
• Model Usage Recommendation: Suggests using the model with the encoder_no_repeat_ngram_size argument.

📦 Installation

No specific installation steps are provided in the original document.

💻 Usage Examples

Basic Usage

# This is a paraphraser for Russian sentences described [in this Habr post](https://habr.com/ru/post/564916/). 
# It is recommended to use the model with the `encoder_no_repeat_ngram_size` argument:
from transformers import T5ForConditionalGeneration, T5Tokenizer
MODEL_NAME = 'cointegrated/rut5-base-paraphraser'
model = T5ForConditionalGeneration.from_pretrained(MODEL_NAME)
tokenizer = T5Tokenizer.from_pretrained(MODEL_NAME)
model.cuda();
model.eval();

def paraphrase(text, beams=5, grams=4, do_sample=False):
    x = tokenizer(text, return_tensors='pt', padding=True).to(model.device)
    max_size = int(x.input_ids.shape[1] * 1.5 + 10)
    out = model.generate(**x, encoder_no_repeat_ngram_size=grams, num_beams=beams, max_length=max_size, do_sample=do_sample)
    return tokenizer.decode(out[0], skip_special_tokens=True)

print(paraphrase('Каждый охотник желает знать, где сидит фазан.'))
# Все охотники хотят знать где фазан сидит.

📚 Documentation

The model is described in this Habr post.

📄 License

This project is licensed under the MIT license.

💡 Usage Tip

It is recommended to use the model with the encoder_no_repeat_ngram_size argument.