https://github.com/bbycroft/llm-viz

3D Visualization of an GPT-style LLM
https://github.com/bbycroft/llm-viz

Last synced: 10 days ago
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3D Visualization of an GPT-style LLM

• Host: GitHub
• URL: https://github.com/bbycroft/llm-viz
• Owner: bbycroft
• Created: 2023-03-01T08:24:43.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-08-24T23:41:32.000Z (3 months ago)
• Last Synced: 2024-08-25T00:34:32.960Z (3 months ago)
• Language: TypeScript
• Homepage: https://bbycroft.net
• Size: 5.74 MB
• Stars: 3,638
• Watchers: 31
• Forks: 402
• Open Issues: 11
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome-ChatGPT-repositories - llm-viz - 3D Visualization of an GPT-style LLM (NLP)
• awesome-web-visualizations - 3D Visualization of an GPT-style LLM

README

        

# Brendan Bycroft's Home Page & Projects

This repository contains my (Brendan's) homepage, as well as a number of non-trivial projects.

They are kept in a single repository for ease of deployment, as well as sharing a bunch of js utils

which are otherwise a pain to share around.

## Projects

The main projects are:

* LLM Visualization: 3D interactive model of a GPT-style LLM network running inference.

* [WIP] CPU Simulation: A 2D digital schematic editor with full a execution model, showcasing a simple

  RISC-V based CPU

### LLM Visualization

This project displays a 3D model of a working implementation of a GPT-style network. That

is, the network topology that's used in OpenAI's GPT-2, GPT-3, (and maybe GPT-4).

The first network displayed with working weights is a tiny such network, which sorts a small list

of the letters A, B, and C. This is the demo example model from Andrej Karpathy's

[minGPT](https://github.com/karpathy/minGPT) implementation.

The renderer also supports visualizing arbitrary sized networks, and works with the smaller gpt2

size, although the weights aren't downloaded (it's 100's of MBs).

### CPU Simulation (WIP; not exposed yet!)

This project runs 2D schematic digital circuits, with a fully fledged editor. The intent is to

add a number of walkthroughs, showing things such as:

  * how a simple RISC-V CPU is constructed

  * the constituent parts down to gate level: instruction decode, ALU, add, etc

  * higher level CPU ideas, like various levels of pipelining, caching, etc

## Running Locally

1. Install dependencies: `yarn`

1. Start the dev server: `yarn dev`