Opus Mt Ru En

🚀 opus-mt-ru-en

A Russian-to-English translation model developed by the Language Technology Research Group at the University of Helsinki.

🚀 Quick Start

To start using the opus-mt-ru-en model, you can use the following code:

from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-ru-en")

model = AutoModelForSeq2SeqLM.from_pretrained("Helsinki-NLP/opus-mt-ru-en")

✨ Features

This model can be used for translation and text-to-text generation.

📚 Documentation

🔍 Model Details

• Developed by: Language Technology Research Group at the University of Helsinki
• Model Type: Transformer-align
• Language(s):
  • Source Language: Russian
  • Target Language: English
• License: CC-BY-4.0
• Resources for more information:
  • GitHub Repo

💼 Uses

Direct Use

This model can be used for translation and text-to-text generation.

⚠️ Risks, Limitations and Biases

⚠️ Important Note

Readers should be aware this section contains content that is disturbing, offensive, and can propagate historical and current stereotypes.

Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)).

Further details about the dataset for this model can be found in the OPUS readme: ru-en

🏋️ Training

Training Data

Preprocessing

• Pre-processing: Normalization + SentencePiece
• Dataset: opus
• Download original weights: opus-2020-02-26.zip
• Test set translations: opus-2020-02-26.test.txt

📊 Evaluation

Results

• test set scores: opus-2020-02-26.eval.txt

Benchmarks

📖 Citation Information

@InProceedings{TiedemannThottingal:EAMT2020,
  author = {J{\"o}rg Tiedemann and Santhosh Thottingal},
  title = {{OPUS-MT} — {B}uilding open translation services for the {W}orld},
  booktitle = {Proceedings of the 22nd Annual Conferenec of the European Association for Machine Translation (EAMT)},
  year = {2020},
  address = {Lisbon, Portugal}
 }