Helsinki-NLP
/
opus-mt-ru-en
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
Helsinki-NLP/opus-mt-ru-en is a forked repo from huggingface. License: cc-by-4-0
31 Commits 1 Branch 0 Tags 1.1 GiB
Go to file
Joao Gante 39fdcea592 Adding generation config file(s) 2023-01-24 15:41:29 +00:00
.gitattributes initial commit 2020-04-29 13:40:09 +00:00
README.md Update README.md 2022-07-14 08:56:05 +00:00
config.json Add TF weights 2022-09-05 12:00:27 +00:00
generation_config.json Adding generation config file(s) 2023-01-24 15:41:29 +00:00
pytorch_model.bin Update pytorch_model.bin 2020-04-29 13:40:09 +00:00
rust_model.ot Update rust_model.ot 2020-05-27 15:23:35 +00:00
source.spm Update source.spm 2020-04-29 13:40:21 +00:00
target.spm Update target.spm 2020-04-29 13:40:21 +00:00
tf_model.h5 Add TF weights 2022-09-05 12:00:27 +00:00
tokenizer_config.json Update tokenizer_config.json 2020-04-29 13:40:21 +00:00
vocab.json Update vocab.json 2020-04-29 13:40:22 +00:00

README.md

tags license
translation
cc-by-4.0

opus-mt-ru-en

Table of Contents

Model Details

Model Description:

  • 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:

Uses

Direct Use

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

Risks, Limitations and Biases

CONTENT WARNING: 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

Evaluation

Results

Benchmarks

testset BLEU chr-F
newstest2012.ru.en 34.8 0.603
newstest2013.ru.en 27.9 0.545
newstest2014-ruen.ru.en 31.9 0.591
newstest2015-enru.ru.en 30.4 0.568
newstest2016-enru.ru.en 30.1 0.565
newstest2017-enru.ru.en 33.4 0.593
newstest2018-enru.ru.en 29.6 0.565
newstest2019-ruen.ru.en 31.4 0.576
Tatoeba.ru.en 61.1 0.736

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}
 }

How to Get Started With the Model

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")