# -*- coding: utf-8 -*-
# SPDX-FileCopyrightText: 2016-2024 PyThaiNLP Project
# SPDX-License-Identifier: Apache-2.0
"""
Thai-French Machine Translation
Trained by OPUS Corpus
Model is from Language Technology Research Group at the University of Helsinki
BLEU 20.4
- Huggingface https://huggingface.co/Helsinki-NLP/opus-mt-th-fr
"""
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
[docs]class ThFrTranslator:
"""
Thai-French Machine Translation
Trained by OPUS Corpus
Model is from Language Technology Research Group at the University of Helsinki
BLEU 20.4
- Huggingface https://huggingface.co/Helsinki-NLP/opus-mt-th-fr
:param bool use_gpu : load model using GPU (Default is False)
"""
[docs] def __init__(
self,
use_gpu: bool = False,
pretrained: str = "Helsinki-NLP/opus-mt-th-fr",
) -> None:
self.tokenizer_thzh = AutoTokenizer.from_pretrained(pretrained)
self.model_thzh = AutoModelForSeq2SeqLM.from_pretrained(pretrained)
if use_gpu:
self.model_thzh = self.model_thzh.cuda()
[docs] def translate(self, text: str) -> str:
"""
Translate text from Thai to French
:param str text: input text in source language
:return: translated text in target language
:rtype: str
:Example:
Translate text from Thai to French::
from pythainlp.translate.th_fr import ThFrTranslator
thfr = ThFrTranslator()
thfr.translate("ทดสอบระบบ")
# output: "Test du système."
"""
self.translated = self.model_thzh.generate(
**self.tokenizer_thzh(text, return_tensors="pt", padding=True)
)
return [
self.tokenizer_thzh.decode(t, skip_special_tokens=True)
for t in self.translated
][0]