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Embedding

A learned dense vector representation that maps discrete tokens to continuous vector spaces.

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Understanding microGPT Walk through Karpathy's 200-line GPT implementation — from autograd and tokenization to multi-head attention, training, and text generation.
Understanding Makemore Build character-level language models from scratch — from bigram counting through MLPs, batch normalization, and WaveNet — generating new names with PyTorch.

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What Is a GPT? Understanding GPT / The Big Picture
A Bigram Language Model Understanding GPT / The Bigram Baseline
Queries, Keys, and Values Understanding GPT / Self-Attention
The Neural Bigram Understanding Makemore / Bigrams
Embeddings and Context Understanding Makemore / The MLP Language Model
The Full Backward Pass Understanding Makemore / Becoming a Backprop Ninja
What Is microGPT? Understanding microGPT / The Big Picture
Backpropagation Understanding microGPT / Automatic Differentiation
Embeddings: Tokens and Positions Understanding microGPT / The Transformer Architecture
Loss and Next-Token Prediction Understanding microGPT / Training
The Training Loop Understanding microGPT / Training
From Micrograd to PyTorch Understanding Micrograd / The Full Picture

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