<?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>Transformers on giuliapl personal page &amp; blog</title><link>https://giuliapl.github.io/tags/transformers/</link><description>Recent content in Transformers on giuliapl personal page &amp; blog</description><generator>Hugo -- 0.156.0</generator><language>en-en</language><lastBuildDate>Fri, 15 May 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://giuliapl.github.io/tags/transformers/index.xml" rel="self" type="application/rss+xml"/><item><title>Writing One Attention Head in NumPy</title><link>https://giuliapl.github.io/posts/attention-in-transformers/</link><pubDate>Fri, 15 May 2026 00:00:00 +0000</pubDate><guid>https://giuliapl.github.io/posts/attention-in-transformers/</guid><description>Implementing a single self-attention head in ~30 lines of NumPy. What surfaces when you write the math by hand: the role of √d_k, where the causal mask goes, and why the row/column convention is the thing that actually trips you up.</description></item></channel></rss>