Instruction: Discuss the key components and steps involved in implementing a transformer model, including attention mechanisms, positional encoding, and layer normalization.
Context: This question assesses the candidate's deep understanding of the transformer architecture and their ability to implement it from the ground up for a specific NLP application.
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I would start by scoping the task, tokenization, architecture size, training objective, and data pipeline before writing layers. Then I would implement the core transformer components: embeddings, positional information, attention blocks, feed-forward layers, masking, and the task-specific output head....