readme: ---
  language: ko
  license: apache-2.0
  tags:
    - korean
  ---
  
  # KoELECTRA (Base Generator)
  
  Pretrained ELECTRA Language Model for Korean (`koelectra-base-generator`)
  
  For more detail, please see [original repository](https://github.com/monologg/KoELECTRA/blob/master/README_EN.md).
  
  ## Usage
  
  ### Load model and tokenizer
  
  ```python
  >>> from transformers import ElectraModel, ElectraTokenizer
  
  >>> model = ElectraModel.from_pretrained("monologg/koelectra-base-generator")
  >>> tokenizer = ElectraTokenizer.from_pretrained("monologg/koelectra-base-generator")
  ```
  
  ### Tokenizer example
  
  ```python
  >>> from transformers import ElectraTokenizer
  >>> tokenizer = ElectraTokenizer.from_pretrained("monologg/koelectra-base-generator")
  >>> tokenizer.tokenize("[CLS] 한국어 ELECTRA를 공유합니다. [SEP]")
  ['[CLS]', '한국어', 'E', '##L', '##EC', '##T', '##RA', '##를', '공유', '##합니다', '.', '[SEP]']
  >>> tokenizer.convert_tokens_to_ids(['[CLS]', '한국어', 'E', '##L', '##EC', '##T', '##RA', '##를', '공유', '##합니다', '.', '[SEP]'])
  [2, 18429, 41, 6240, 15229, 6204, 20894, 5689, 12622, 10690, 18, 3]
  ```
  
  ## Example using ElectraForMaskedLM
  
  ```python
  from transformers import pipeline
  
  fill_mask = pipeline(
      "fill-mask",
      model="monologg/koelectra-base-generator",
      tokenizer="monologg/koelectra-base-generator"
  )
  
  print(fill_mask("나는 {} 밥을 먹었다.".format(fill_mask.tokenizer.mask_token)))
  ```
  