docs: update readme

README.md

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+---
+language: ko
+---
+
+# KoELECTRA v2 (Base Generator)
+
+Pretrained ELECTRA Language Model for Korean (`koelectra-base-v2-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-v2-generator")
+>>> tokenizer = ElectraTokenizer.from_pretrained("monologg/koelectra-base-v2-generator")
+```
+
+### Tokenizer example
+
+```python
+>>> from transformers import ElectraTokenizer
+>>> tokenizer = ElectraTokenizer.from_pretrained("monologg/koelectra-base-v2-generator")
+>>> tokenizer.tokenize("[CLS] 한국어 ELECTRA를 공유합니다. [SEP]")
+['[CLS]', '한국어', 'EL', '##EC', '##TRA', '##를', '공유', '##합니다', '.', '[SEP]']
+>>> tokenizer.convert_tokens_to_ids(['[CLS]', '한국어', 'EL', '##EC', '##TRA', '##를', '공유', '##합니다', '.', '[SEP]'])
+[2, 5084, 16248, 3770, 19059, 29965, 2259, 10431, 5, 3]
+```
+
+## Example using ElectraForMaskedLM
+
+```python
+from transformers import pipeline
+
+fill_mask = pipeline(
+    "fill-mask",
+    model="monologg/koelectra-base-v2-generator",
+    tokenizer="monologg/koelectra-base-v2-generator"
+)
+
+print(fill_mask("나는 {} 밥을 먹었다.".format(fill_mask.tokenizer.mask_token)))
+```