<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Language-Models on DATATWEETS</title><link>https://datatweets.com/tags/language-models/</link><description>Recent content in Language-Models on DATATWEETS</description><generator>Hugo</generator><language>en</language><copyright>Copyright (c) 2026 Datatweets</copyright><lastBuildDate>Tue, 14 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://datatweets.com/tags/language-models/index.xml" rel="self" type="application/rss+xml"/><item><title>Causal Self-Attention in NumPy: Stop Future-Token Leakage</title><link>https://datatweets.com/tutorials/causal-self-attention-numpy/</link><pubDate>Tue, 14 Jul 2026 00:00:00 +0000</pubDate><guid>https://datatweets.com/tutorials/causal-self-attention-numpy/</guid><description>A beginner-friendly NumPy lesson on the triangular mask used by next-token models. Compare masked and unmasked attention, inspect real weights, and verify causality by changing a future token.</description></item></channel></rss>