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BERT-base talking heads + ggelu | uncased_L-12_H-768_A-12 | Wiki + Books | [talkheads_ggelu_base](https://tfhub.dev/tensorflow/talkheads_ggelu_bert_en_base/1) | BERT-base trained with [talking heads attention](https://arxiv.org/abs/2003.02436) and [gated GeLU](https://arxiv.org/abs/2002.05202).
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BERT-large talking heads + ggelu | uncased_L-24_H-1024_A-16 | Wiki + Books | [talkheads_ggelu_large](https://tfhub.dev/tensorflow/talkheads_ggelu_bert_en_large/1) | BERT-large trained with [talking heads attention](https://arxiv.org/abs/2003.02436) and [gated GeLU](https://arxiv.org/abs/2002.05202).
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LAMBERT-large uncased English | uncased_L-24_H-1024_A-16 | Wiki + Books | [lambert](https://tfhub.dev/tensorflow/lambert_en_uncased_L-24_H-1024_A-16/1) | BERT trained with LAMB and techniques from RoBERTa.
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## ALBERT
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The academic paper that describes ALBERT in detail and provides full results on
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a number of tasks can be found here: https://arxiv.org/abs/1909.11942.
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We released both checkpoints and tf.hub modules as the pretrained models for
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fine-tuning. They are TF 2.x compatible and are converted from the ALBERT v2
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checkpoints released in the TF 1.x official ALBERT repository
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