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🤯 Did You Know (click to read)
The Transformer architecture eliminated recurrence entirely, allowing full sequence parallelization for faster training.
The encoder captures source sentence representations using self-attention, while the decoder generates the target sequence attending to encoder outputs. This architecture enables accurate context-dependent translation over long sequences, surpassing prior recurrent models.
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💥 Impact (click to read)
Transformer-based translation improves fluency, accuracy, and training speed for multilingual NLP applications.
Language learners and global businesses benefit from AI-powered translation tools based on Transformer models.
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