<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Posts on Sidney Fletcher</title><link>https://sidneyfletcher.com/posts/</link><description>Recent content in Posts on Sidney Fletcher</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Thu, 20 Aug 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://sidneyfletcher.com/posts/index.xml" rel="self" type="application/rss+xml"/><item><title>Understanding LLMs From Scratch: Tokenizers</title><link>https://sidneyfletcher.com/understanding-llms-from-scratch-tokenizers/</link><pubDate>Thu, 20 Aug 2026 00:00:00 +0000</pubDate><guid>https://sidneyfletcher.com/understanding-llms-from-scratch-tokenizers/</guid><description>&lt;p&gt;You wake up, Rip Van Winkle-like, from a deep sleep. It&amp;rsquo;s 2026 and LLM&amp;rsquo;s are taking over the world. Time to learn something about how these work, you think (and write up your notes).&lt;/p&gt;
&lt;p&gt;Best to start at the very beginning of the LLM processing pipeline - what is a tokenizer and how does it work?&lt;/p&gt;
&lt;h2 id="what-are-tokenizers"&gt;What are Tokenizers?&lt;/h2&gt;
&lt;p&gt;At its most basic, a tokenizer is a way to take a string of text and turn it into a list of numbers that a computer can understand.&lt;/p&gt;</description></item></channel></rss>