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--- |
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language: |
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- zh |
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tags: |
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- translation |
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- 文言文 |
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- ancient |
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license: apache-2.0 |
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datasets: |
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- cctc |
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widget: |
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- text: "如果不除掉他，之后会是个隐患" |
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--- |
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# From modern Chinese to Ancient Chinese |
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> 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 |
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> 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) |
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## 推荐的inference 通道 |
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```python |
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from transformers import ( |
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EncoderDecoderModel, |
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AutoTokenizer |
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) |
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PRETRAINED = "raynardj/wenyanwen-chinese-translate-to-ancient" |
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tokenizer = AutoTokenizer.from_pretrained(PRETRAINED) |
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model = EncoderDecoderModel.from_pretrained(PRETRAINED) |
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def inference(text): |
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tk_kwargs = dict( |
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truncation=True, |
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max_length=128, |
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padding="max_length", |
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return_tensors='pt') |
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inputs = tokenizer([text,],**tk_kwargs) |
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with torch.no_grad(): |
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return tokenizer.batch_decode( |
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model.generate( |
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inputs.input_ids, |
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attention_mask=inputs.attention_mask, |
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num_beams=3, |
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bos_token_id=101, |
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eos_token_id=tokenizer.sep_token_id, |
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pad_token_id=tokenizer.pad_token_id, |
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), skip_special_tokens=True) |
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``` |
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## 目前版本的案例 |
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```python |
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>>> inference('你连一百块都不肯给我') |
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['不 肯 与 我 百 钱 。'] |
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``` |
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```python |
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>>> inference("他不能做长远的谋划") |
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['不 能 为 远 谋 。'] |
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``` |
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```python |
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>>> inference("我们要干一番大事业") |
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['吾 属 当 举 大 事 。'] |
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``` |
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```python |
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>>> inference("这感觉，已经不对，我努力，在挽回") |
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['此 之 谓 也 ， 已 不 可 矣 ， 我 勉 之 ， 以 回 之 。'] |
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``` |
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```python |
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>>> 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") |
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['轻 我 行 ， 如 我 轻 来 ， 挥 袂 不 携 一 片 云 。'] |
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``` |
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