
# roberta-classical-chinese-base-char

## Model Description

This is a RoBERTa model pre-trained on Classical Chinese texts, derived from [GuwenBERT-base](https://huggingface.co/ethanyt/guwenbert-base). Character-embeddings are enhanced into traditional/simplified characters. You can fine-tune `roberta-classical-chinese-base-char` for downstream tasks, such as [sentence-segmentation](https://huggingface.co/KoichiYasuoka/roberta-classical-chinese-base-sentence-segmentation), [POS-tagging](https://huggingface.co/KoichiYasuoka/roberta-classical-chinese-base-upos), [dependency-parsing](https://huggingface.co/KoichiYasuoka/roberta-classical-chinese-base-ud-goeswith), and so on.

## How to Use

```py
from transformers import AutoTokenizer,AutoModelForMaskedLM
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/roberta-classical-chinese-base-char")
model=AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/roberta-classical-chinese-base-char")
```

## See Also

[SuPar-Kanbun](https://github.com/KoichiYasuoka/SuPar-Kanbun): Tokenizer POS-tagger and Dependency-parser for Classical Chinese


{"language": ["lzh"], "license": "apache-2.0", "tags": ["classical chinese", "literary chinese", "ancient chinese", "masked-lm"], "pipeline_tag": "fill-mask", "mask_token": "[MASK]", "widget": [{"text": "\u5b5f\u5b50[MASK]\u6881\u60e0\u738b"}]}
transformers pytorch roberta fill-mask classical chinese literary chinese ancient chinese masked-lm lzh license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #fill-mask #classical chinese #literary chinese #ancient chinese #masked-lm #lzh #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 


# roberta-classical-chinese-base-char

## Model Description

This is a RoBERTa model pre-trained on Classical Chinese texts, derived from GuwenBERT-base. Character-embeddings are enhanced into traditional/simplified characters. You can fine-tune 'roberta-classical-chinese-base-char' for downstream tasks, such as sentence-segmentation, POS-tagging, dependency-parsing, and so on.

## How to Use



## See Also

SuPar-Kanbun: Tokenizer POS-tagger and Dependency-parser for Classical Chinese


# roberta-classical-chinese-base-char ## Model Description

This is a RoBERTa model pre-trained on Classical Chinese texts, derived from GuwenBERT-base. Character-embeddings are enhanced into traditional/simplified characters. You can fine-tune 'roberta-classical-chinese-base-char' for downstream tasks, such as sentence-segmentation, POS-tagging, dependency-parsing, and so on. ## How to Use ## See Also

SuPar-Kanbun: Tokenizer POS-tagger and Dependency-parser for Classical Chinese
TAGS
#transformers #pytorch #roberta #fill-mask #classical chinese #literary chinese #ancient chinese #masked-lm #lzh #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # roberta-classical-chinese-base-char ## Model Description

This is a RoBERTa model pre-trained on Classical Chinese texts, derived from GuwenBERT-base. Character-embeddings are enhanced into traditional/simplified characters. You can fine-tune 'roberta-classical-chinese-base-char' for downstream tasks, such as sentence-segmentation, POS-tagging, dependency-parsing, and so on. ## How to Use ## See Also

SuPar-Kanbun: Tokenizer POS-tagger and Dependency-parser for Classical Chinese
passage: TAGS
#transformers #pytorch #roberta #fill-mask #classical chinese #literary chinese #ancient chinese #masked-lm #lzh #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# roberta-classical-chinese-base-char## Model Description

This is a RoBERTa model pre-trained on Classical Chinese texts, derived from GuwenBERT-base. Character-embeddings are enhanced into traditional/simplified characters. You can fine-tune 'roberta-classical-chinese-base-char' for downstream tasks, such as sentence-segmentation, POS-tagging, dependency-parsing, and so on.## How to Use## See Also

SuPar-Kanbun: Tokenizer POS-tagger and Dependency-parser for Classical Chinese