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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
# 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")
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# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kykim/bertshared-kor-base") model = AutoModelForSeq2SeqLM.from_pretrained("kykim/bertshared-kor-base")