S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)

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A transformer-based masked language model for learning amino acid sequence representations. The model uses self-attention mechanisms with custom gating and incorporates protein features for enhanced sequence understanding. Trained using BERT-style masking on peptide sequences to learn contextual amino acid embeddings.