Huggingface Tranformers🤗 라이브러리를 이용하여 구현tokenization_kobert.py에서 KoBertTokenizer를 임포트해야 합니다.from transformers import BertModel
from tokenization_kobert import KoBertTokenizer
model = BertModel.from_pretrained('monologg/kobert')
tokenizer = KoBertTokenizer.from_pretrained('monologg/kobert')
$ python3 main.py --model_type kobert --do_train --do_eval
$ python3 predict.py --input_file {INPUT_FILE_PATH} --output_file {OUTPUT_FILE_PATH} --model_dir {SAVED_CKPT_PATH}
| Accuracy (%) | |
|---|---|
| KoBERT | 89.63 |
| DistilKoBERT | 88.41 |
| Bert-Multilingual | 87.07 |
| FastText | 85.50 |
26 commits
Python
100.0%
Huggingface Tranformers🤗 라이브러리를 이용하여 구현tokenization_kobert.py에서 KoBertTokenizer를 임포트해야 합니다.from transformers import BertModel
from tokenization_kobert import KoBertTokenizer
model = BertModel.from_pretrained('monologg/kobert')
tokenizer = KoBertTokenizer.from_pretrained('monologg/kobert')
$ python3 main.py --model_type kobert --do_train --do_eval
$ python3 predict.py --input_file {INPUT_FILE_PATH} --output_file {OUTPUT_FILE_PATH} --model_dir {SAVED_CKPT_PATH}
| Accuracy (%) | |
|---|---|
| KoBERT | 89.63 |
| DistilKoBERT | 88.41 |
| Bert-Multilingual | 87.07 |
| FastText | 85.50 |
26 commits
Python
100.0%