Transformer · 学 AI | 投机取巧

解决什么问题What problem it solves

当前所有主流大模型共用的底层架构。The architecture underneath every mainstream large model today.

这是什么What it is

一种神经网络结构，核心是「注意力机制」，用来处理一整段文本之间的关系。

它能并行处理整句话，而不是一个词一个词往后读——这是它能训练出万亿参数规模的原因。

A neural network structure built around the attention mechanism, handling the relationships across a whole passage of text.

It processes a sentence in parallel rather than one word at a time — which is why it scales to trillions of parameters.

为什么需要知道Why it matters

它是大模型的「根」。理解它，你才能理解上下文窗口、幻觉、KV 缓存这些概念从哪来。It is the root of large models. Understand it and the origin of context windows, hallucination and the KV cache becomes clear.

接着读什么，为什么What to read next, and why

注意力机制Attention
看架构中的一项具体计算机制。Inspect a concrete mechanism within the architecture.
训练三阶段SFT → Reward Model → RL
在《一个下午看懂原理》中接着读Continue in “One Afternoon Under the Hood”
嵌入层Embedding Layer
在《一个下午看懂原理》中接着读Continue in “One Afternoon Under the Hood”

现在能做什么What you can do now

去 Models 图谱：看这个模型有哪些量化版、按你的显存该下哪一档Models atlas: which quantisations exist and which tier fits your VRAM ↗

回到名词地图看第4站的其他 35 个词 →Back to the map: the other 35 terms in station 4 →

出处Sources

Attention Is All You Need（论文）Attention Is All You Need (paper) ↗
Hugging Face 课程（Transformer）How do Transformers work? (Hugging Face NLP course) ↗

TransformerTransformer