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README.md
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AntiBERTa2 is an antibody-specific language model based on the [RoFormer model](https://arxiv.org/abs/2104.09864) - it is pre-trained using masked language modelling.
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We also provide a multimodal version of AntiBERTa2, AntiBERTa2-CSSP, that has been trained using a contrastive objective, similar to the [CLIP method](https://arxiv.org/abs/2103.00020).
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Further details on both AntiBERTa2 and AntiBERTa2-CSSP are described in our [paper]() accepted at the NeurIPS MLSB Workshop 2023.
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Both AntiBERTa2 models are only available for non-commercial use. Output antibody sequences (e.g. from infilling via masked language models) can only be used for
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non-commercial use. For any users seeking commercial use of our model and generated antibodies, please reach out to us at [[email protected]](mailto:[email protected]).
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AntiBERTa2 is an antibody-specific language model based on the [RoFormer model](https://arxiv.org/abs/2104.09864) - it is pre-trained using masked language modelling.
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We also provide a multimodal version of AntiBERTa2, AntiBERTa2-CSSP, that has been trained using a contrastive objective, similar to the [CLIP method](https://arxiv.org/abs/2103.00020).
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Further details on both AntiBERTa2 and AntiBERTa2-CSSP are described in our [paper](https://www.mlsb.io/papers_2023/Enhancing_Antibody_Language_Models_with_Structural_Information.pdf) accepted at the NeurIPS MLSB Workshop 2023.
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Both AntiBERTa2 models are only available for non-commercial use. Output antibody sequences (e.g. from infilling via masked language models) can only be used for
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non-commercial use. For any users seeking commercial use of our model and generated antibodies, please reach out to us at [[email protected]](mailto:[email protected]).
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