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From modern Chinese to Ancient Chinese

This model translate modern Chinese to Classical Chinese, so I guess who's interested in the problemset can speak at least modern Chinese, so... let me continue the documentation in Chinese

推荐的inference 通道

注意, 你必须将generate函数的eos_token_id设置为102就可以翻译出完整的语句, 不然翻译完了会有残留的语句(因为做熵的时候用pad标签=-100导致)。

目前huggingface 页面上compute按钮会有这个问题, 推荐使用以下代码来得到翻译结果🎻

from transformers import (
  EncoderDecoderModel,
  AutoTokenizer
)
PRETRAINED = "raynardj/wenyanwen-chinese-translate-to-ancient"
tokenizer = AutoTokenizer.from_pretrained(PRETRAINED)
model = EncoderDecoderModel.from_pretrained(PRETRAINED)

def inference(text):
    tk_kwargs = dict(
      truncation=True,
      max_length=128,
      padding="max_length",
      return_tensors='pt')
   
    inputs = tokenizer([text,],**tk_kwargs)
    with torch.no_grad():
        return tokenizer.batch_decode(
            model.generate(
            inputs.input_ids,
            attention_mask=inputs.attention_mask,
            num_beams=3,
            bos_token_id=101,
            eos_token_id=tokenizer.sep_token_id,
            pad_token_id=tokenizer.pad_token_id,
        ), skip_special_tokens=True)

目前版本的案例

大家如果有好玩的调戏案例, 也欢迎反馈

>>> inference('你连一百块都不肯给我')
['不 肯 与 我 百 钱 。']
>>> inference("他不能做长远的谋划")
['不 能 为 远 谋 。']
>>> inference("我们要干一番大事业")
['吾 属 当 举 大 事 。']
>>> inference("这感觉,已经不对,我努力,在挽回")
['此 之 谓 也 , 已 不 可 矣 , 我 勉 之 , 以 回 之 。']
>>> inference("轻轻地我走了, 正如我轻轻地来, 我挥一挥衣袖,不带走一片云彩")
['轻 我 行 , 如 我 轻 来 , 挥 袂 不 携 一 片 云 。']

其他文言诗词的资源

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