<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:sy="http://purl.org/rss/1.0/modules/syndication/" xmlns:media="http://search.yahoo.com/mrss/"><channel><title>Token on Shaowen Chen's Website</title><link>https://www.chenshaowen.com/en/tags/token/</link><description>Recent content in Token on Shaowen Chen's Website</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>&amp;copy;2016 - {year}, All Rights Reserved.</copyright><lastBuildDate>Tue, 10 Sep 2024 10:00:00 +0000</lastBuildDate><sy:updatePeriod>weekly</sy:updatePeriod><atom:link href="https://www.chenshaowen.com/en/tags/token/atom.xml" rel="self" type="application/rss+xml"/><item><title>What Is a Token</title><link>https://www.chenshaowen.com/en/blog/what-is-token.html</link><pubDate>Tue, 10 Sep 2024 10:00:00 +0000</pubDate><atom:modified>Tue, 10 Sep 2024 10:00:00 +0000</atom:modified><guid>https://www.chenshaowen.com/en/blog/what-is-token.html</guid><description>A token is a unit tightly bound to data. It can be used to measure how much corpus is needed to train a model, and also to measure the input and output length at inference time. 1. What a token is A token can be a whole word, a subword,</description><dc:creator>WeChat Official Account</dc:creator><category>Machine Learning</category><category>LLM</category><category>AI</category><category>Token</category><category>Learning</category><category>NLP</category><category>Inference</category></item></channel></rss>