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Building Domain-Specific LLMs: Examples and Techniques Transformers use parallel multi-head attention, affording more ability to encode nuances of word meanings. A self-attention mechanism helps the LLM learn the associations between concepts and words. Transformers also utilize layer normalization, residual and feedforward connections, and positional embeddings. Open-source...