IndoBERT Large Model (phase1 uncased) IndoBERT is a state of the art language model for Indonesian based on the BERT model. The pretrained model is trained using a masked language modeling (MLM) objective and next sentence prediction (NSP) objective. All Pre trained Models Model params Arch. Training data indobenchmark/indobert base p1 124.5M Base Indo4B (23.43 GB of text) indobenchmark/indobert base p2 124.5M Base Indo4B (23.43 GB of text) indobenchmark/indobert large p1 335.2M Large Indo4B (23.43 GB of text) indobenchmark/indobert large p2 335.2M Large Indo4B (23.43 GB of text) indobenchmark/indobert lite base p1 11.7M Base Indo4B (23.43 GB of text) indobenchmark/indobert lite base p2 11.7M Base Indo4B (23.43 GB of text) indobenchmark/indobert lite large p1 17.7M Large Indo4B (23.43 GB of text) indobenchmark/indobert lite large p2 17.7M Large Indo4B (23.43 GB of text) How to use Load model and tokenizer Extract contextual representation Authors IndoBERT was trained and evaluated by Bryan Wilie\ , Karissa Vincentio\ , Genta Indra Winata\ , Samuel Cahyawijaya\ , Xiaohong Li, Zhi Yuan Lim, Sidik Soleman, Rahmad Mahendra, Pascale Fung, Syafri Bahar, Ayu Purwarianti. Citation If you u…
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