
# roberta-classical-chinese-large-upos

## Model Description

This is a RoBERTa model pre-trained on Classical Chinese texts for POS-tagging and dependency-parsing, derived from [roberta-classical-chinese-large-char](https://huggingface.co/KoichiYasuoka/roberta-classical-chinese-large-char). 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 AutoTokenizer,AutoModelForTokenClassification
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-classical-chinese-large-upos")
model=AutoModelForTokenClassification.from_pretrained("KoichiYasuoka/roberta-classical-chinese-large-upos")
```
or

```py
import esupar
nlp=esupar.load("KoichiYasuoka/roberta-classical-chinese-large-upos")
```

## Reference

Koichi Yasuoka: [Universal Dependencies Treebank of the Four Books in Classical Chinese](http://hdl.handle.net/2433/245217), DADH2019: 10th International Conference of Digital Archives and Digital Humanities (December 2019), pp.20-28.

## See Also

[esupar](https://github.com/KoichiYasuoka/esupar): Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models


{"language": ["lzh"], "license": "apache-2.0", "tags": ["classical chinese", "literary chinese", "ancient chinese", "token-classification", "pos", "dependency-parsing"], "datasets": ["universal_dependencies"], "pipeline_tag": "token-classification", "widget": [{"text": "\u5b50\u66f0\u5b78\u800c\u6642\u7fd2\u4e4b\u4e0d\u4ea6\u8aac\u4e4e\u6709\u670b\u81ea\u9060\u65b9\u4f86\u4e0d\u4ea6\u6a02\u4e4e\u4eba\u4e0d\u77e5\u800c\u4e0d\u614d\u4e0d\u4ea6\u541b\u5b50\u4e4e"}]}
transformers pytorch roberta token-classification classical chinese literary chinese ancient chinese pos dependency-parsing lzh dataset:universal_dependencies license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #token-classification #classical chinese #literary chinese #ancient chinese #pos #dependency-parsing #lzh #dataset-universal_dependencies #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 


# roberta-classical-chinese-large-upos

## Model Description

This is a RoBERTa model pre-trained on Classical Chinese texts for POS-tagging and dependency-parsing, derived from roberta-classical-chinese-large-char. Every word is tagged by UPOS (Universal Part-Of-Speech) and FEATS.

## How to Use


or



## Reference

Koichi Yasuoka: Universal Dependencies Treebank of the Four Books in Classical Chinese, DADH2019: 10th International Conference of Digital Archives and Digital Humanities (December 2019), pp.20-28.

## See Also

esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models


# roberta-classical-chinese-large-upos ## Model Description

This is a RoBERTa model pre-trained on Classical Chinese texts for POS-tagging and dependency-parsing, derived from roberta-classical-chinese-large-char. Every word is tagged by UPOS (Universal Part-Of-Speech) and FEATS. ## How to Use


or ## Reference

Koichi Yasuoka: Universal Dependencies Treebank of the Four Books in Classical Chinese, DADH2019: 10th International Conference of Digital Archives and Digital Humanities (December 2019), pp.20-28. ## See Also

esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models
TAGS
#transformers #pytorch #roberta #token-classification #classical chinese #literary chinese #ancient chinese #pos #dependency-parsing #lzh #dataset-universal_dependencies #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # roberta-classical-chinese-large-upos ## Model Description

This is a RoBERTa model pre-trained on Classical Chinese texts for POS-tagging and dependency-parsing, derived from roberta-classical-chinese-large-char. Every word is tagged by UPOS (Universal Part-Of-Speech) and FEATS. ## How to Use


or ## Reference

Koichi Yasuoka: Universal Dependencies Treebank of the Four Books in Classical Chinese, DADH2019: 10th International Conference of Digital Archives and Digital Humanities (December 2019), pp.20-28. ## See Also

esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models
passage: TAGS
#transformers #pytorch #roberta #token-classification #classical chinese #literary chinese #ancient chinese #pos #dependency-parsing #lzh #dataset-universal_dependencies #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# roberta-classical-chinese-large-upos## Model Description

This is a RoBERTa model pre-trained on Classical Chinese texts for POS-tagging and dependency-parsing, derived from roberta-classical-chinese-large-char. Every word is tagged by UPOS (Universal Part-Of-Speech) and FEATS.## How to Use


or## Reference

Koichi Yasuoka: Universal Dependencies Treebank of the Four Books in Classical Chinese, DADH2019: 10th International Conference of Digital Archives and Digital Humanities (December 2019), pp.20-28.## See Also

esupar: Tokenizer POS-tagger and Dependency-parser with BERT/RoBERTa/DeBERTa models