opus mt fr en
Overview
Highlights
- Dedicated bidirectional French-English translation capabilities
- Permissive Apache-2.0 license for commercial use
- Low-latency performance compared to general LLMs
- Optimized for self-hosting and local deployment
- Developed by trusted Helsinki-NLP research team
Usage
# Install Hugging Face transformers
pip install transformers torch
# Load model with transformers
from transformers import AutoModel, AutoTokenizer
model = AutoModel.from_pretrained("Helsinki-NLP/opus-mt-fr-en")
tokenizer = AutoTokenizer.from_pretrained("Helsinki-NLP/opus-mt-fr-en")
Hugging Face Download
We recommend downloading the model via the Hugging Face CLI or Hub SDK.
Guidance:Before downloading, install huggingface_hub with:
pip install -U huggingface_hub
CLI Download
Download the full repository
huggingface-cli download Helsinki-NLP/opus-mt-fr-en
Download a single file to a local folder (e.g. config.json into ./dir)
huggingface-cli download Helsinki-NLP/opus-mt-fr-en config.json --local-dir ./dir
See the official docs for more CLI options
SDK Download
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('Helsinki-NLP/opus-mt-fr-en')
Git Download
Make sure git-lfs is installed first
git lfs install
git clone https://huggingface.co/Helsinki-NLP/opus-mt-fr-en
To skip LFS large-file downloads, use:
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/Helsinki-NLP/opus-mt-fr-en
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
pip install -U transformers torch
Load the model and run inference
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained('Helsinki-NLP/opus-mt-fr-en')
tokenizer = AutoTokenizer.from_pretrained('Helsinki-NLP/opus-mt-fr-en')
Model Download
We recommend downloading the model via the ModelScope CLI or SDK.
Guidance:Before downloading, install ModelScope with:
pip install modelscope
CLI Download
Download the full repository
modelscope download --model Helsinki-NLP/opus-mt-fr-en
Download a single file to a local folder (e.g. README.md into ./dir)
modelscope download --model Helsinki-NLP/opus-mt-fr-en README.md --local_dir ./dir
See the docs for more CLI options
SDK Download
# 模型下载
from modelscope import snapshot_download
model_dir = snapshot_download('Helsinki-NLP/opus-mt-fr-en')
Git Download
Make sure git-lfs is installed first
git lfs install
git clone https://www.modelscope.cn/Helsinki-NLP/opus-mt-fr-en.git
To skip LFS large-file downloads, use:
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/Helsinki-NLP/opus-mt-fr-en.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
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
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
p = pipeline('text-generation', 'Helsinki-NLP/opus-mt-fr-en')
Full Documentation
---
tags:
- translation
license: apache-2.0
---
opus-mt-fr-en
- source languages: fr
- target languages: en
- OPUS readme: fr-en
- dataset: opus
- model: transformer-align
- pre-processing: normalization + SentencePiece
- download original weights: opus-2020-02-26.zip
- test set translations: opus-2020-02-26.test.txt
- test set scores: opus-2020-02-26.eval.txt
Benchmarks
| testset | BLEU | chr-F |
|-----------------------|-------|-------|
| newsdiscussdev2015-enfr.fr.en | 33.1 | 0.580 |
| newsdiscusstest2015-enfr.fr.en | 38.7 | 0.614 |
| newssyscomb2009.fr.en | 30.3 | 0.569 |
| news-test2008.fr.en | 26.2 | 0.542 |
| newstest2009.fr.en | 30.2 | 0.570 |
| newstest2010.fr.en | 32.2 | 0.590 |
| newstest2011.fr.en | 33.0 | 0.597 |
| newstest2012.fr.en | 32.8 | 0.591 |
| newstest2013.fr.en | 33.9 | 0.591 |
| newstest2014-fren.fr.en | 37.8 | 0.633 |
| Tatoeba.fr.en | 57.5 | 0.720 |