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Chinese Simplified and Traditional, \n\n12-layer, 768-hidden, 12-heads, 110M parameters"},"_id":"64ff6000e3201fff883b4b18"},{"author":"google-bert","authorData":{"avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/5dd96eb166059660ed1ee413/TmmBAiyUIfm_mM3OtySkw.png","fullname":"BERT community","name":"google-bert","type":"org","isHf":false,"isMod":false,"isEnterprise":false,"followerCount":167},"downloads":6288,"gated":false,"id":"google-bert/bert-large-cased-whole-word-masking","inference":"not-popular-enough","lastModified":"2024-04-10T09:56:46.000Z","likes":15,"pipeline_tag":"fill-mask","private":false,"repoType":"model","isLikedByUser":false,"widgetOutputUrls":[],"type":"model","position":7,"note":{"html":"Large BERT model, larger variant. Trained on the \"cased\" dataset, meaning that it wasn't lowercase and all accents were kept.\n\nWhole word masking indicates a different preprocessing where entire words are masked rather than subwords. The BERT team reports better metrics with the wwm models.\n\n24-layer, 1024-hidden, 16-heads, 340M parameters","text":"Large BERT model, larger variant. Trained on the \"cased\" dataset, meaning that it wasn't lowercase and all accents were kept.\n\nWhole word masking indicates a different preprocessing where entire words are masked rather than subwords. The BERT team reports better metrics with the wwm models.\n\n24-layer, 1024-hidden, 16-heads, 340M parameters"},"_id":"64ff633970b6b05c5ab14be1"},{"author":"google-bert","authorData":{"avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/5dd96eb166059660ed1ee413/TmmBAiyUIfm_mM3OtySkw.png","fullname":"BERT community","name":"google-bert","type":"org","isHf":false,"isMod":false,"isEnterprise":false,"followerCount":167},"downloads":28615,"gated":false,"id":"google-bert/bert-large-uncased-whole-word-masking","inference":"not-popular-enough","lastModified":"2024-02-19T11:08:36.000Z","likes":19,"pipeline_tag":"fill-mask","private":false,"repoType":"model","isLikedByUser":false,"widgetOutputUrls":[],"type":"model","position":8,"note":{"html":" Large BERT model, larger variant. 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google 's Collections

BERT release

Regroups the original BERT models released by the Google team. Except for the models marked otherwise, the checkpoints support English.