GPT in 500 Lines of SQL

The author delves into how large language models are implemented in SQL, using GPT2 as an example. They explain the process of tokenizing text using Byte Pair Encoding to convert it into numbers that neural networks can interpret efficiently. The author provides SQL code snippets to showcase how this tokenization process works, breaking down complex words into smaller tokens to reduce the space needed for calculations. The implementation involves recursive queries to merge tokens and optimize text encoding. The author’s unique approach of using SQL for language model implementation showcases a clever use of technology and programming to achieve complex tasks.

https://explainextended.com/2023/12/31/happy-new-year-15/

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