| |
| |
| |
| |
| """ |
| Lalita Chinese-Thai Machine Translation |
| |
| from AI builder |
| |
| - GitHub: https://github.com/LalitaDeelert/lalita-mt-zhth |
| - Facebook post https://web.facebook.com/aibuildersx/posts/166736255494822 |
| """ |
| from transformers import AutoModelForSeq2SeqLM, AutoTokenizer |
|
|
|
|
| class ThZhTranslator: |
| """ |
| Thai-Chinese Machine Translation |
| |
| from Lalita @ AI builder |
| |
| - GitHub: https://github.com/LalitaDeelert/lalita-mt-zhth |
| - Facebook post https://web.facebook.com/aibuildersx/posts/166736255494822 |
| |
| :param bool use_gpu : load model using GPU (Default is False) |
| """ |
|
|
| def __init__( |
| self, |
| use_gpu: bool = False, |
| pretrained: str = "Lalita/marianmt-th-zh_cn", |
| ) -> 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 Chinese |
| |
| :param str text: input text in source language |
| :return: translated text in target language |
| :rtype: str |
| |
| :Example: |
| |
| Translate text from Thai to Chinese:: |
| |
| from pythainlp.translate import ThZhTranslator |
| |
| thzh = ThZhTranslator() |
| |
| thzh.translate("ผมรักคุณ") |
| # output: 我爱你 |
| |
| """ |
| 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] |
|
|
|
|
| class ZhThTranslator: |
| """ |
| Chinese-Thai Machine Translation |
| |
| from Lalita @ AI builder |
| |
| - GitHub: https://github.com/LalitaDeelert/lalita-mt-zhth |
| - Facebook post https://web.facebook.com/aibuildersx/posts/166736255494822 |
| |
| :param bool use_gpu : load model using GPU (Default is False) |
| """ |
|
|
| def __init__( |
| self, |
| use_gpu: bool = False, |
| pretrained: str = "Lalita/marianmt-zh_cn-th", |
| ) -> None: |
| self.tokenizer_zhth = AutoTokenizer.from_pretrained(pretrained) |
| self.model_zhth = AutoModelForSeq2SeqLM.from_pretrained(pretrained) |
| if use_gpu: |
| self.model_zhth.cuda() |
|
|
| def translate(self, text: str) -> str: |
| """ |
| Translate text from Chinese to Thai |
| |
| :param str text: input text in source language |
| :return: translated text in target language |
| :rtype: str |
| |
| :Example: |
| |
| Translate text from Chinese to Thai:: |
| |
| from pythainlp.translate import ZhThTranslator |
| |
| zhth = ZhThTranslator() |
| |
| zhth.translate("我爱你") |
| # output: ผมรักคุณนะ |
| |
| """ |
| self.translated = self.model_zhth.generate( |
| **self.tokenizer_zhth(text, return_tensors="pt", padding=True) |
| ) |
| return [ |
| self.tokenizer_zhth.decode(t, skip_special_tokens=True) |
| for t in self.translated |
| ][0] |
|
|
