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Outcome School · Transformers and architecture14 min read

by Amit Shekhar · 15 April 2026

Decoding Vision Transformer (ViT)

The Vision Transformer (ViT) by decoding how it splits an image into patches, turns those patches into tokens, and processes them with a transformer to classify the image.

2,711 words#ai#machine-learning4 recall cards

Decoding Vision Transformer (ViT)
Read on Outcome School ↗then come back to lock it in
Before you read, guess

What are the sequential steps for processing an image in a Vision Transformer?

Ten seconds, a guess, then read — a wrong guess still makes the answer stick.

What this article covers

  1. The Big Picture
  2. Decoding Step 1: Splitting the Image into Patches
  3. Decoding Step 2: Patch Embedding
  4. Decoding Step 3: The CLS Token
  5. Decoding Step 4: Position Embeddings
  6. Decoding Step 5: The Transformer Encoder
  7. Decoding Step 6: The Classification Head
  8. Putting It All Together
  9. ViT vs CNN

The article lives on outcomeschool.com. Read it there, then come back: the tutor in the margin has read it and will answer questions, and the questions below check what stayed.

Before you go

In one sentence, what was this chapter about?

From memory, without scrolling up. Writing it is what makes it yours; the grade is only to show you what you had.

How sure?