Llama from scratch (or how to implement a paper without crying)

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A developer shares tips for implementing a scaled-down version of Meta's Llama language model using TinyShakespeare data. The process involves iteratively building and testing model components, starting with a simple feed-forward network and gradually adding Llama-specific features like RMSNorm, rotary embeddings, and SwiGLU activation. The final model achieves low loss and generates coherent Shakespeare-like text.