opus mt en ru

ProviderHelsinki-NLP
Categorytranslation
Licenseapache-2.0
Downloads122
Stars0

Overview

Opus-MT EN-RU is a specialized neural machine translation model developed by Helsinki-NLP, designed specifically for high-efficiency English-to-Russian translation. Unlike general-purpose LLMs, this model is lightweight and focused, making it ideal for developers who need low-latency translation without the overhead of a massive parameter count. It is fully open-source under the Apache-2.0 license, allowing for seamless integration into commercial pipelines and local deployment via the Hugging Face Transformers library. For developers building localized apps or automated documentation workflows, Opus-MT provides a predictable, fast, and cost-effective alternative to expensive proprietary APIs.

Highlights

  • Optimized for high-speed English to Russian translation
  • Permissive Apache-2.0 license for commercial use
  • Low resource overhead for local edge deployment
  • Easy integration via Hugging Face Transformers library

Usage

Install
# Install Hugging Face transformers
pip install transformers torch
SDK Usage
# Load model with transformers
from transformers import AutoModel, AutoTokenizer

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

Hugging Face Download

We recommend downloading the model via the Hugging Face CLI or Hub SDK.

Guidance:Before downloading, install huggingface_hub with:

Guidance
pip install -U huggingface_hub

CLI Download

Download the full repository

Download the full repository
huggingface-cli download Helsinki-NLP/opus-mt-en-ru

Download a single file to a local folder (e.g. config.json into ./dir)

Download a single file to a local folder (e.g. config.json into ./dir)
huggingface-cli download Helsinki-NLP/opus-mt-en-ru config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

SDK Download
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('Helsinki-NLP/opus-mt-en-ru')

Git Download

Make sure git-lfs is installed first

Git Download
git lfs install
git clone https://huggingface.co/Helsinki-NLP/opus-mt-en-ru

To skip LFS large-file downloads, use:

Skip LFS
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/Helsinki-NLP/opus-mt-en-ru

Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.

PyTorch / Transformers Usage

Install Transformers

Install Transformers
pip install -U transformers torch

Load the model and run inference

Load the model and run inference
from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('Helsinki-NLP/opus-mt-en-ru')
tokenizer = AutoTokenizer.from_pretrained('Helsinki-NLP/opus-mt-en-ru')

Model Download

We recommend downloading the model via the ModelScope CLI or SDK.

Guidance:Before downloading, install ModelScope with:

Guidance
pip install modelscope

CLI Download

Download the full repository

Download the full repository
modelscope download --model Helsinki-NLP/opus-mt-en-ru

Download a single file to a local folder (e.g. README.md into ./dir)

Download a single file to a local folder (e.g. README.md into ./dir)
modelscope download --model Helsinki-NLP/opus-mt-en-ru README.md --local_dir ./dir

See the docs for more CLI options

SDK Download

SDK Download
# 模型下载
from modelscope import snapshot_download
model_dir = snapshot_download('Helsinki-NLP/opus-mt-en-ru')

Git Download

Make sure git-lfs is installed first

Git Download
git lfs install
git clone https://www.modelscope.cn/Helsinki-NLP/opus-mt-en-ru.git

To skip LFS large-file downloads, use:

Skip LFS
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/Helsinki-NLP/opus-mt-en-ru.git

ModelScope 模型页直接下载模型文件;无需将模型文件放在本站服务器。

Notebook Quickstart

Install the ModelScope library

Install the ModelScope library
pip install "modelscope[audio,cv,nlp,multi-modal,science]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html

Load the model and run inference

Load the model and run inference
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks

p = pipeline('text-generation', 'Helsinki-NLP/opus-mt-en-ru')

Full Documentation

来源: HuggingFace

---
tags:

  • translation

license: apache-2.0
---

opus-mt-en-ru

  • source languages: en
  • target languages: ru
  • dataset: opus
  • model: transformer-align
  • pre-processing: normalization + SentencePiece

Benchmarks

| testset | BLEU | chr-F |
|-----------------------|-------|-------|
| newstest2012.en.ru | 31.1 | 0.581 |
| newstest2013.en.ru | 23.5 | 0.513 |
| newstest2015-enru.en.ru | 27.5 | 0.564 |
| newstest2016-enru.en.ru | 26.4 | 0.548 |
| newstest2017-enru.en.ru | 29.1 | 0.572 |
| newstest2018-enru.en.ru | 25.4 | 0.554 |
| newstest2019-enru.en.ru | 27.1 | 0.533 |
| Tatoeba.en.ru | 48.4 | 0.669 |

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