metadata
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
推荐的inference 通道
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
>>> 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 。']