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A comprehensive technical survey and implementation guide of sequence modeling evolution. Features mathematical foundations and PyTorch implementations of RNNs, LSTMs, GRUs, and Transformers, exploring the transition from sequential recurrence to parallelized self-attention and modern LLM scaling laws.