opus mt fr en
简介
核心亮点
- 专注法英互译,翻译风格地道且精准
- 轻量化架构,支持低成本本地化部署
- Apache-2.0 协议,企业级商用无压力
- 响应延迟极低,适合高频自动化翻译场景
使用方法
# 安装 Hugging Face transformers
pip install transformers torch
# 使用 transformers 加载模型
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 下载
我们推荐使用命令行或者 Hugging Face Hub SDK 来进行模型的下载。
操作指引:在下载前,请先通过如下命令安装 huggingface_hub:
pip install -U huggingface_hub
命令行下载
下载完整模型库
huggingface-cli download Helsinki-NLP/opus-mt-fr-en
下载单个文件到指定本地文件夹(以下载 config.json 到当前路径下 ./dir 目录为例)
huggingface-cli download Helsinki-NLP/opus-mt-fr-en config.json --local-dir ./dir
SDK 下载
# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('Helsinki-NLP/opus-mt-fr-en')
Git 下载
请确保 lfs 已经被正确安装
git lfs install
git clone https://huggingface.co/Helsinki-NLP/opus-mt-fr-en
如果您希望跳过 lfs 大文件下载,可以使用如下命令
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/Helsinki-NLP/opus-mt-fr-en
模型文件托管在 Hugging Face Hub,使用 HF CLI / SDK / Git 直接下载,不经过本站。
PyTorch / Transformers 使用
安装 Transformers
pip install -U transformers torch
模型加载和推理
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')
模型下载
我们推荐使用命令行或者 ModelScope SDK 来进行模型的下载。
操作指引:在下载前,请先通过如下命令安装 ModelScope:
pip install modelscope
命令行下载
下载完整模型库
modelscope download --model Helsinki-NLP/opus-mt-fr-en
下载单个文件到指定本地文件夹(以下载 README.md 到当前路径下 dir 目录为例)
modelscope download --model Helsinki-NLP/opus-mt-fr-en README.md --local_dir ./dir
SDK 下载
# 模型下载
from modelscope import snapshot_download
model_dir = snapshot_download('Helsinki-NLP/opus-mt-fr-en')
Git 下载
请确保 lfs 已经被正确安装
git lfs install
git clone https://www.modelscope.cn/Helsinki-NLP/opus-mt-fr-en.git
如果您希望跳过 lfs 大文件下载,可以使用如下命令
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 快速开发
下载并安装 ModelScope library
pip install "modelscope[audio,cv,nlp,multi-modal,science]" -f https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html
模型加载和推理
from modelscope.pipelines import pipeline
from modelscope.utils.constant import Tasks
p = pipeline('text-generation', 'Helsinki-NLP/opus-mt-fr-en')
完整文档
---
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 |