<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>TransformerLens on Text Matrix</title><link>https://txtmix.com/tags/transformerlens/</link><description>Recent content in TransformerLens on Text Matrix</description><generator>Hugo</generator><language>zh-cn</language><lastBuildDate>Tue, 21 Jul 2026 20:06:14 +0800</lastBuildDate><atom:link href="https://txtmix.com/tags/transformerlens/index.xml" rel="self" type="application/rss+xml"/><item><title>transformerlens-skill：将 TransformerLens 机制可解释性工作流模块化</title><link>https://txtmix.com/posts/tech/transformerlens-skill-modular-mechanistic-interpretability/</link><pubDate>Sun, 17 May 2026 12:04:00 +0800</pubDate><guid>https://txtmix.com/posts/tech/transformerlens-skill-modular-mechanistic-interpretability/</guid><description>&lt;h2 id="项目概览">项目概览&lt;/h2>
&lt;p>&lt;strong>transformerlens-skill&lt;/strong>（&lt;a href="https://github.com/Durararananke/transformerlens_skill" target="_blank" rel="noopener noreffer ">Durararananke/transformerlens_skill&lt;/a>）是一个基于 TransformerLens 框架的机制可解释性（Mechanistic Interpretability）工具库。它把激活缓存、因果追踪、归因修补（Attribution Patching）、对数透镜（Logit Lens）和激活 Steering 等常见分析范式封装成了独立模块，研究者可以直接调用而不需要每次从零写 boilerplate。&lt;/p></description></item></channel></rss>