README.md

---
language:
- zh
tags:
- translation
- 文言文
- ancient
license: apache-2.0
datasets:
- cctc
widget:
- text: "如果不除掉他，之后会是个隐患"

---

# 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

> 从现代文到文言文的翻译器, 训练语料是就是九十多万句句对， [数据集链接](https://github.com/BangBOOM/Classical-Chinese)

## 推荐的inference 通道
```python
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
```python
>>> inference('你连一百块都不肯给我')
['不 肯 与 我 百 钱 。']
```

```python
>>> inference("他不能做长远的谋划")
['不 能 为 远 谋 。']
```

```python
>>> inference("我们要干一番大事业")
['吾 属 当 举 大 事 。']
```

```python
>>> 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 。']
```

```python
>>> 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 。']
```