<?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 danilchenko.dev</title><link>https://www.danilchenko.dev/tags/transformers/</link><description>Recent content in Transformers on danilchenko.dev</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Tue, 30 Jun 2026 08:24:33 +0000</lastBuildDate><atom:link href="https://www.danilchenko.dev/tags/transformers/index.xml" rel="self" type="application/rss+xml"/><item><title>Sparse Attention Explained: How LLMs Handle Million-Token Contexts Without Melting Your GPU</title><link>https://www.danilchenko.dev/posts/sparse-attention-explained/</link><pubDate>Tue, 30 Jun 2026 08:24:33 +0000</pubDate><guid>https://www.danilchenko.dev/posts/sparse-attention-explained/</guid><description>How sparse attention cuts LLM inference cost by 10x on long contexts. Covers DeepSeek NSA, MInference, H2O, and The Sparse Frontier&amp;#39;s findings.</description></item></channel></rss>