https://spreadsheets-are-all-you-need.ai/index.html

Spreadsheets are all you need.ai

A low-code way to learn AI

Learn how AI works from a real LLM implemented entirely in Excel

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Watch the 10 min demo from the Seattle AI Tinkerers meetup

Sophisticated yet simple

Spreadsheets-are-all-you-need is a low-code introduction to the
details behind today's Large Language Models (LLMs) that's ideal for:

  * Technical executives, marketers, and product managers
  * Developers and scientists transitioning into machine learning
  * AI policy makers and ethicists

If you can understand a spreadsheet, then you can understand AI!

[GPT2-at-a-glance]
[GPT2-at-a-glance-overview]

Learn from a real LLM

Spreadsheets-are-all-you-need implements the forward pass of GPT2 (an
ancestor of ChatGPT that was state of the art only a few years ago)
entirely in Excel using standard spreadsheet functions.

This same Transformer architecture is the foundation for OpenAI's
ChatGPT, Anthropic's Claude, Google's Bard/Gemini, Meta's Llama, and
many other LLMs.

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    Yesterday I knew nothing about how AI works. But today that
    changed thanks to these two awesome resources @karpathy's Intro
    to Large Language Models: https://t.co/gcWxKwdI0U@ianand's
    Spreadsheets-are-all-you-need: https://t.co/E9LIZDOQ9A

    I'm constantly consuming...

    -- mert (@mertduzgun_) February 25, 2024

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More lessons to come! Get notified!

Future videos will walk through more details on the internals of
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Watch the lessons

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Lesson 1: Demystifying GPT with Excel

In this 10-minute video we kick things off by walking through the
high-level architecture of GPT-2 and witnessing each phase of the
Transformer come to life in an Excel spreadsheet.

Lesson 2: Byte Pair Encoding & Tokenization

In this lesson we dive into the first phase of GPT, the tokenization
phase and the Byte Pair Encoding (BPE) algorithm used in models like
ChatGPT. We cover

  * Detailed walkthrough of the BPE algorithm, including its learning
    phase and application in language data tokenization.
  * Spreadsheet Simulation: A hands-on demonstration of the GPT-2's
    tokenization process via a spreadsheet model.
  * Limitations and Alternatives: Discussion on the challenges of BPE
    and a look at other tokenization methods.

Extra: An end-to-end walk through of the Excel sheet

This is a high level walk through of the Excel implementation. It is
primarily geared to those who already understand Transformers and
want to know how the standard architecture is mapped to the
spreadsheet.

Try it yourself

Downloading

The sheet is available as an xlsb (Excel binary) file in the Releases
section of the github repo. You should be able to download and run
this file in Excel for Mac or PC.

Using

If you're quickly trying to orient yourself to the spreadsheet this
walk through video may be helpful though it is not oriented to
beginners. For beginners, it's recommended to start with the lesson
videos.

Please realize the implementation is just enough to run very small
workloads:

  * Full GPT2 small (124M parameters) model including byte pair
    encoding, embeddings, multi-headed attention, and multi-layer
    perceptron stages
  * Inference/forward pass only (no training)
  * Context is limited to 10 tokens in length
  * 10 characters per word limit
  * Zero temperature output only

This sheet is very big. Unfortunately, it is not unusual for Excel to
lock up (but only on a Mac) while using this spreadsheet. It is
highly recommended to use the manual calculation mode in Excel and
the Windows version of Excel (either on a Windows directory or via
Parallels on a Mac).

Issues

Bugs are not out of the question. Please file issues on Github

Contact

@ianand on Twitter

ianand/spreadsheets-are-all-you-need on Github

FAQ

What about Google Sheets?

This project actually started on Google Sheets but the full 124M
model was too big and switched to Excel. I'm still exploring ways to
make this work in Google Sheets but it is unlikely to fit into a
single file as it can with Excel.

Why can't I chat with it like ChatGPT? It doesn't match the output of
ChatGPT?

Aside from the minuscule context length, it also lacks the
instruction tuning and reinforcement learning from human feedback
(RLHF) that turn a large language model into a chatbot.

Why is it called Spreadsheets-are-all-you-need

The name is a play on the title of the famous Attention Is All You
Need paper which first described the Transformer machine learning
architecture that underlies ChatGPT, Claude, Bard, and many of the
latest Generative AI tools.

Spreadsheets are all you need.ai

A low-code way to learn AI