
# bert-base-japanese-char-extended

## Model Description

This is a BERT model pre-trained on Japanese Wikipedia texts, derived from [bert-base-japanese-char-v2](https://huggingface.co/cl-tohoku/bert-base-japanese-char-v2). Character-embeddings are enhanced to include all 常用漢字/人名用漢字 characters using BertTokenizerFast. You can fine-tune `bert-base-japanese-char-extended` for downstream tasks, such as [POS-tagging](https://huggingface.co/KoichiYasuoka/bert-base-japanese-upos), [dependency-parsing](https://huggingface.co/KoichiYasuoka/bert-base-japanese-wikipedia-ud-head), and so on.

## How to Use

```py
from transformers import AutoTokenizer,AutoModelForMaskedLM
tokenizer=AutoTokenizer.from_pretrained("KoichiYasuoka/bert-base-japanese-char-extended")
model=AutoModelForMaskedLM.from_pretrained("KoichiYasuoka/bert-base-japanese-char-extended")
```


{"language": ["ja"], "license": "cc-by-sa-4.0", "tags": ["japanese", "masked-lm", "wikipedia"], "pipeline_tag": "fill-mask", "mask_token": "[MASK]", "widget": [{"text": "\u9178\u7d20\u30dc\u30f3\u30d9\u3092\u5145[MASK]\u3059\u308b\u3002"}]}
transformers pytorch bert fill-mask japanese masked-lm wikipedia ja license:cc-by-sa-4.0 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #bert #fill-mask #japanese #masked-lm #wikipedia #ja #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 


# bert-base-japanese-char-extended

## Model Description

This is a BERT model pre-trained on Japanese Wikipedia texts, derived from bert-base-japanese-char-v2. Character-embeddings are enhanced to include all 常用漢字/人名用漢字 characters using BertTokenizerFast. You can fine-tune 'bert-base-japanese-char-extended' for downstream tasks, such as POS-tagging, dependency-parsing, and so on.

## How to Use




# bert-base-japanese-char-extended ## Model Description

This is a BERT model pre-trained on Japanese Wikipedia texts, derived from bert-base-japanese-char-v2. Character-embeddings are enhanced to include all 常用漢字/人名用漢字 characters using BertTokenizerFast. You can fine-tune 'bert-base-japanese-char-extended' for downstream tasks, such as POS-tagging, dependency-parsing, and so on. ## How to Use
TAGS
#transformers #pytorch #bert #fill-mask #japanese #masked-lm #wikipedia #ja #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # bert-base-japanese-char-extended ## Model Description

This is a BERT model pre-trained on Japanese Wikipedia texts, derived from bert-base-japanese-char-v2. Character-embeddings are enhanced to include all 常用漢字/人名用漢字 characters using BertTokenizerFast. You can fine-tune 'bert-base-japanese-char-extended' for downstream tasks, such as POS-tagging, dependency-parsing, and so on. ## How to Use
passage: TAGS
#transformers #pytorch #bert #fill-mask #japanese #masked-lm #wikipedia #ja #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #has_space #region-us 
# bert-base-japanese-char-extended## Model Description

This is a BERT model pre-trained on Japanese Wikipedia texts, derived from bert-base-japanese-char-v2. Character-embeddings are enhanced to include all 常用漢字/人名用漢字 characters using BertTokenizerFast. You can fine-tune 'bert-base-japanese-char-extended' for downstream tasks, such as POS-tagging, dependency-parsing, and so on.## How to Use