| from transformers import M2M100ForConditionalGeneration | |
| from .tokenization_small100 import SMALL100Tokenizer | |
| class Small100Translator: | |
| """ | |
| Machine Translation using small100 model | |
| - Huggingface https://huggingface.co/alirezamsh/small100 | |
| :param bool use_gpu : load model using GPU (Default is False) | |
| """ | |
| def __init__( | |
| self, | |
| use_gpu: bool = False, | |
| pretrained: str = "alirezamsh/small100", | |
| ) -> None: | |
| self.pretrained = pretrained | |
| self.model = M2M100ForConditionalGeneration.from_pretrained(self.pretrained) | |
| self.tgt_lang = None | |
| if use_gpu: | |
| self.model = self.model.cuda() | |
| def translate(self, text: str, tgt_lang: str="en") -> str: | |
| """ | |
| Translate text from X to X | |
| :param str text: input text in source language | |
| :param str tgt_lang: target language | |
| :return: translated text in target language | |
| :rtype: str | |
| :Example: | |
| :: | |
| from pythainlp.translate.small100 import Small100Translator | |
| mt = Small100Translator() | |
| # Translate text from Thai to English | |
| mt.translate("ทดสอบระบบ", tgt_lang="en") | |
| # output: 'Testing system' | |
| # Translate text from Thai to Chinese | |
| mt.translate("ทดสอบระบบ", tgt_lang="zh") | |
| # output: '系统测试' | |
| # Translate text from Thai to French | |
| mt.translate("ทดสอบระบบ", tgt_lang="fr") | |
| # output: 'Test du système' | |
| """ | |
| if tgt_lang!=self.tgt_lang: | |
| self.tokenizer = SMALL100Tokenizer.from_pretrained(self.pretrained, tgt_lang=tgt_lang) | |
| self.tgt_lang = tgt_lang | |
| self.translated = self.model.generate( | |
| **self.tokenizer(text, return_tensors="pt") | |
| ) | |
| return self.tokenizer.batch_decode(self.translated, skip_special_tokens=True)[0] | |