Transformer Architecture: Multi Headed Attention explained
Multi-Headed Attention in Transformer architecture is like having multiple spotlights shining on different parts of a sentence simultaneously. It allows the model to capture various types of relationships and dependencies between words, improving its understanding of context and meaning.
In simpler terms: It's like a team of experts analyzing the same text from different perspectives, each focusing on a specific aspect. This helps the model gain a more comprehensive understanding of the text, leading to better language processing and generation.
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