
# Bert base model for Korean

* 70GB Korean text dataset and 42000 lower-cased subwords are used
* Check the model performance and other language models for Korean in [github](https://github.com/kiyoungkim1/LM-kor)

```python
# only for pytorch in transformers
from transformers import BertTokenizerFast, EncoderDecoderModel

tokenizer = BertTokenizerFast.from_pretrained("kykim/bertshared-kor-base")
model = EncoderDecoderModel.from_pretrained("kykim/bertshared-kor-base")
```
{"language": "ko"}
transformers pytorch encoder-decoder text2text-generation ko autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #encoder-decoder #text2text-generation #ko #autotrain_compatible #endpoints_compatible #has_space #region-us 


# Bert base model for Korean

* 70GB Korean text dataset and 42000 lower-cased subwords are used
* Check the model performance and other language models for Korean in github


# Bert base model for Korean

* 70GB Korean text dataset and 42000 lower-cased subwords are used
* Check the model performance and other language models for Korean in github
TAGS
#transformers #pytorch #encoder-decoder #text2text-generation #ko #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # Bert base model for Korean

* 70GB Korean text dataset and 42000 lower-cased subwords are used
* Check the model performance and other language models for Korean in github
passage: TAGS
#transformers #pytorch #encoder-decoder #text2text-generation #ko #autotrain_compatible #endpoints_compatible #has_space #region-us 
# Bert base model for Korean

* 70GB Korean text dataset and 42000 lower-cased subwords are used
* Check the model performance and other language models for Korean in github