| |
| |
| |
| |
| """ |
| 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 AutoModelForSeq2SeqLM, AutoTokenizer |
|
|
|
|
| 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) |
| """ |
|
|
| 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() |
|
|
| 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] |
|
|
