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---
language:
- "lzh"
tags:
- "classical chinese"
- "literary chinese"
- "ancient chinese"
- "token-classification"
- "pos"
- "dependency-parsing"
datasets:
- "universal_dependencies"
license: "apache-2.0"
pipeline_tag: "token-classification"
widget:
- text: "子曰學而時習之不亦説乎有朋自遠方來不亦樂乎人不知而不慍不亦君子乎"
---
# Xunzi-Qwen1.5-7B-upos
## Model Description
This is a Qwen1.5 model pre-trained on Classical Chinese texts for POS-tagging, derived from [Xunzi-Qwen1.5-7B](https://www.modelscope.cn/models/Xunzillm4cc/Xunzi-Qwen1.5-7B). Every word is tagged by [UPOS](https://universaldependencies.org/u/pos/) (Universal Part-Of-Speech) and [FEATS](https://universaldependencies.org/u/feat/).
## How to Use
```py
from transformers import pipeline
nlp=pipeline("upos","KoichiYasuoka/Xunzi-Qwen1.5-7B-upos",trust_remote_code=True,aggregation_strategy="simple")
print(nlp("不入虎穴不得虎子"))
```
## Reference
安岡孝一: [GPT系モデルの系列ラベリングによる品詞付与](http://hdl.handle.net/2433/288964), 東洋学へのコンピュータ利用, 第38回研究セミナー (2024年7月26日), pp.3-10.
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