Chapter 8: RMS Normalisation and Residual Connections
What You'll Build Two architectural patterns that make deep networks trainable: RMSNorm (keeps activations from exploding or vanishing) and residual c…
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Chapter 7: The Training Loop and Adam Optimiser
What You'll Build A complete training loop that processes documents, computes loss, backpropagates gradients, and updates parameters using the Adam op…
Without google's transformers, there is no GPT-ishs
Yes, remember back there in 2020/2021 when OpenAI created the gpt2? How about we really focus on what enable them to do that? google transformers. The…
Chapter 5: Linear Transformation and Softmax
What You'll Build Two helper functions that show up in nearly every layer of a neural network: Linear takes an input vector and a weight matrix, multi…