Model Card for kobart base v2 Model Details Model Description BART ( B idirectional and A uto R egressive T ransformers)는 입력 텍스트 일부에 노이즈를 추가하여 이를 다시 원문으로 복구하는 autoencoder 의 형태로 학습이 됩니다. 한국어 BART(이하 KoBART ) 는 논문에서 사용된 Text Infilling 노이즈 함수를 사용하여 40GB 이상의 한국어 텍스트에 대해서 학습한 한국어 encoder decoder 언어 모델입니다. 이를 통해 도출된 KoBART base 를 배포합니다. Developed by: More information needed Shared by [Optional]: Heewon(Haven) Jeon Model type: Feature Extraction Language(s) (NLP): Korean License: MIT Parent Model: BART Resources for more information: GitHub Repo Model Demo Space Uses Direct Use This model can be used for the task of Feature Extraction. Downstream Use [Optional] More information needed. Out of Scope Use The model should not be used to intentionally create hostile or alienating environments for people. Bias, Risks, and Limitations Significant research has explored bias and fairness issues with language models (see, e.g., Sheng et al. (2021) and Bender et al. (2021)). Predictions generated by the model may include disturbing and harmful stereotypes across protected classes; identity characteristics; and sensitive, social, and occupational groups. Recommendations Users (both direct and downst…
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