Beomi/KcBERT
π€ Pretrained BERT model & WordPiece tokenizer trained on Korean Comments νκ΅μ΄ λκΈλ‘ ν리νΈλ μ΄λν BERT λͺ¨λΈκ³Ό λ°μ΄ν°μ
This project offers specialized AI models designed to understand casual, informal Korean text, particularly online comments. It takes raw Korean user-generated content, like social media comments, and processes it to extract meaning, sentiment, or other insights. This is ideal for market researchers, social media analysts, or customer service managers who need to analyze public opinion and feedback expressed in everyday Korean.
495 stars. No commits in the last 6 months.
Use this if you need to analyze large volumes of Korean online comments, forum posts, or social media discussions to understand sentiment, identify key topics, or categorize user feedback, where standard models struggle with slang, typos, and informal language.
Not ideal if your primary data source consists of formal Korean documents like news articles, academic papers, or official reports, as other models trained on such refined text might be more suitable.
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495
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45
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License
MIT
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Last pushed
Nov 07, 2022
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