用交互式动画展示Transformer模型内部运作机制
AnimatedLLM: Explaining LLMs with Interactive Visualizations
- 在浏览器中运行，通过预计算轨迹可视化Transformer结构
- 支持手动输入的逐层注意力与激活过程展示
- 适合教学或自学者理解大模型内部逻辑
大型语言模型（LLMs）正日益成为自然语言处理教育的核心，但揭示其工作原理的教学材料却十分稀缺。我们提出了AnimatedLLM，一个完全在浏览器中运行的交互式网页应用，可逐步可视化Transformer语言模型的内部机制。该应用使用对公开大模型在精心设计输入上生成的预计算追踪数据，用户可通过交互方式观察模型各层的注意力分布与激活状态。项目已开源，网址为 https://animatedllm.github.io，既可用于课堂教学，也适合自主学习。
原文摘要 · Abstract (English)
Large language models (LLMs) are becoming central to natural language processing education, yet materials showing their mechanics are sparse. We present AnimatedLLM, an interactive web application that provides step-by-step visualizations of a Transformer language model. AnimatedLLM runs entirely in the browser, using pre-computed traces of open LLMs applied on manually curated inputs. The application is available at https://animatedllm.github.io, both as a teaching aid and for self-educational purposes.
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