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update usecase with pipeline on README
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language: ko

Bert base model for Korean

Update

  • Update at 2021.11.17 : Add Native Support for BERT Tokenizer (works with AutoTokenizer, pipeline)

  • 70GB Korean text dataset and 42000 lower-cased subwords are used
  • Check the model performance and other language models for Korean in github
from transformers import pipeline

pipe = pipeline('text-generation', model='beomi/kykim-gpt3-kor-small_based_on_gpt2')
print(pipe("μ•ˆλ…•ν•˜μ„Έμš”! μ˜€λŠ˜μ€"))
# [{'generated_text': 'μ•ˆλ…•ν•˜μ„Έμš”! μ˜€λŠ˜μ€ μ œκ°€ μš”μ¦˜ μ‚¬μš©ν•˜κ³  μžˆλŠ” ν΄λ Œμ§•μ›Œν„°λ₯Ό μ†Œκ°œν•΄λ“œλ¦¬λ €κ³  ν•΄μš”! λ°”λ‘œ 이 μ œν’ˆ!! λ°”λ‘œ 이'}]