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Details will follow ...
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# Chapter 1: Understanding Large Language Models
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There is no code in this chapter.
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# Chapter 2: Working with Text Data
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- [ch02.ipynb](ch02.ipynb) has all the code as it appears in the chapter
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- [dataloader.ipynb](dataloader.ipynb) is a minimal notebook with the main data loading pipeline implemented in this chapter
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# Chapter 2: Working with Text Data
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- [compare-bpe-tiktoken.ipynb](compare-bpe-tiktoken.ipynb) benchmarks various byte pair encoding implementations
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- [bpe_openai_gpt2.py](bpe_openai_gpt2.py) is the original bytepair encoder code used by OpenAI
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# Chapter 2: Working with Text Data
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- [embeddings-and-linear-layers.ipynb](embeddings-and-linear-layers.ipynb) contains optional (bonus) code to explain that embedding layers and fully connected layers applied to one-hot encoded vectors are equivalent.
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# Chapter 2: Working with Text Data
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- [01_main-chapter-code](01_main-chapter-code) contains the main chapter code
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- [02_bonus_bytepair-encoder](02_bonus_bytepair-encoder) contains optional code to benchmark different byte pair encoder implementations
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- [03_bonus_embedding-vs-matmul](03_bonus_embedding-vs-matmul) contains optional (bonus) code to explain that embedding layers and fully connected layers applied to one-hot encoded vectors are equivalent.
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