Transformer Basics: Encoder and Decoder
A clear explanation of what the Transformer encoder and decoder each do, grounded in the original architecture and illustrated with simple examples.
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LLM Learning Basics: cross-entropy and perplexity
Explains cross-entropy and perplexity — the metrics used to measure how wrong a model is — with formulas, commentary, and examples.
LLM Math Basics 2: Softmax and Probability Interpretation
A walkthrough of how softmax converts raw scores into probability-like values, with formulas, explanations, and examples.
LLM Math Basics 1: Vectors and the Dot Product
A walkthrough of vectors and the dot product — with notation, explanations, and examples — covering what you need to know before reading LLM papers.
LLM Paper Evolution Map (MOC)
A Map of Content page for reading core LLM papers in order, starting from the Transformer.