LLM Foundations - LLM Bootcamp

LLM Foundations - LLM Bootcamp

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Why include code in LLM training data?

17 of 19

17 of 19

Why include code in LLM training data?

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Classroom Contents

LLM Foundations - LLM Bootcamp

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  1. 1 Intro
  2. 2 Foundations of Machine Learning
  3. 3 The Transformer Architecture
  4. 4 Transformer Decoder Overview
  5. 5 Inputs
  6. 6 Input Embedding
  7. 7 Masked Multi-Head Attention
  8. 8 Positional Encoding
  9. 9 Skip Connections and Layer Norm
  10. 10 Feed-forward Layer
  11. 11 Transformer hyperparameters and Why they work so well
  12. 12 Notable LLM: BERT
  13. 13 Notable LLM: T5
  14. 14 Notable LLM: GPT
  15. 15 Notable LLM: Chinchilla and Scaling Laws
  16. 16 Notable LLM: LLaMA
  17. 17 Why include code in LLM training data?
  18. 18 Instruction Tuning
  19. 19 Notable LLM: RETRO

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