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language: ko |
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--- |
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# KoELECTRA (Small Discriminator) |
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Pretrained ELECTRA Language Model for Korean (`koelectra-small-discriminator`) |
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For more detail, please see [original repository](https://github.com/monologg/KoELECTRA/blob/master/README_EN.md). |
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## Usage |
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### Load model and tokenizer |
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```python |
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>>> from transformers import ElectraModel, ElectraTokenizer |
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>>> model = ElectraModel.from_pretrained("monologg/koelectra-small-discriminator") |
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>>> tokenizer = ElectraTokenizer.from_pretrained("monologg/koelectra-small-discriminator") |
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``` |
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### Tokenizer example |
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```python |
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>>> from transformers import ElectraTokenizer |
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>>> tokenizer = ElectraTokenizer.from_pretrained("monologg/koelectra-small-discriminator") |
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>>> tokenizer.tokenize("[CLS] 한국어 ELECTRA를 공유합니다. [SEP]") |
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['[CLS]', '한국어', 'E', '##L', '##EC', '##T', '##RA', '##를', '공유', '##합니다', '.', '[SEP]'] |
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>>> tokenizer.convert_tokens_to_ids(['[CLS]', '한국어', 'E', '##L', '##EC', '##T', '##RA', '##를', '공유', '##합니다', '.', '[SEP]']) |
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[2, 18429, 41, 6240, 15229, 6204, 20894, 5689, 12622, 10690, 18, 3] |
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``` |
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## Example using ElectraForPreTraining |
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```python |
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import torch |
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from transformers import ElectraForPreTraining, ElectraTokenizer |
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discriminator = ElectraForPreTraining.from_pretrained("monologg/koelectra-small-discriminator") |
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tokenizer = ElectraTokenizer.from_pretrained("monologg/koelectra-small-discriminator") |
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sentence = "나는 방금 밥을 먹었다." |
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fake_sentence = "나는 내일 밥을 먹었다." |
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fake_tokens = tokenizer.tokenize(fake_sentence) |
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fake_inputs = tokenizer.encode(fake_sentence, return_tensors="pt") |
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discriminator_outputs = discriminator(fake_inputs) |
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predictions = torch.round((torch.sign(discriminator_outputs[0]) + 1) / 2) |
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print(list(zip(fake_tokens, predictions.tolist()[1:-1]))) |
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``` |
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