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AntiBERTa2 License
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Version 1.0, December 2023 [Alchemab](http://alchemab.com)
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AntiBERTa2 models are antibody-specific Large Language Models (LLM) developed by Alchemab Therapeutics Ltd. Currently AntiBERTa2 includes the following two architectures referred to as AntiBERTa2 (220 M parameters) and AntiBERTa2-CSSP (220 M parameters). Based on the RoFormer LLM from natural language processing, AntiBERTa2 is pre-trained using MLM on 779.4 million unpaired and paired antibody sequences. AntiBERTa2-CSSP refers to a multimodal version of the AntiBERTa2 LLM that leverages the contrastive pre-training objective from the CLIP method; over 1000 antibody crystal structures from the Protein Data Bank were used. After pre-training, AntiBERTa2 develops a rich representation of antibody sequences that can be leveraged for an extensive range of tasks, including (without limitation) antigen binding prediction.
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# AntiBERTa2 License
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Version 1.0, December 2023 [Alchemab](http://alchemab.com)
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AntiBERTa2 models are antibody-specific Large Language Models (LLM) developed by Alchemab Therapeutics Ltd. Currently AntiBERTa2 includes the following two architectures referred to as AntiBERTa2 (220 M parameters) and AntiBERTa2-CSSP (220 M parameters). Based on the RoFormer LLM from natural language processing, AntiBERTa2 is pre-trained using MLM on 779.4 million unpaired and paired antibody sequences. AntiBERTa2-CSSP refers to a multimodal version of the AntiBERTa2 LLM that leverages the contrastive pre-training objective from the CLIP method; over 1000 antibody crystal structures from the Protein Data Bank were used. After pre-training, AntiBERTa2 develops a rich representation of antibody sequences that can be leveraged for an extensive range of tasks, including (without limitation) antigen binding prediction.
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