Spreadsheet Is All You Need (Excel version added!)
A fascinating project known as "Spreadsheet Is All You Need" presents an innovative approach to understanding the workings of GPT models. The project creator aimed to visualize and comprehend the complex structure of transformers by constructing a nanoGPT pipeline entirely within a spreadsheet. This approach transforms the learning experience into one that is both interactive and engaging.
Overview
The essence of this project lies in visualizing the intricacies of transformers within a familiar spreadsheet environment. It demystifies how transformers function by breaking them down into easily understandable components and matrices, all configured and calculated within a spreadsheet.
Upon exploring the internal mechanisms of Language Learning Models (LLMs), the creator realized that transformers fundamentally operate through a series of matrix calculations connected in a precise sequence. Driven by curiosity, they explored whether these computations could be replicated in a spreadsheet format, ultimately achieving a full inference pipeline of the nanoGPT architecture using simple spreadsheet tools, foregoing more common programming environments like Python.
Core Components
The spreadsheet encompasses all essential components of a transformer, including:
- Embedding
- Layer Norm
- Self-Attention
- Projection
- MLP (Multi-Layer Perceptron)
- Softmax
- Logits
The model is constructed based on Andrej Karpathy's NanoGPT framework, featuring approximately 85,000 parameters. While modest in size compared to more complex models like ChatGPT, it remains sufficiently intricate to provide a clear understanding of the transformative processes while being manageable for most computers.
Detailed Features
In the provided "nanoGPT.numbers" file, users will find two tabs: "no weights" and "random weights". Both offer the same structural setup, but the parameters in the "random weights" tab are generated randomly each time, whereas the "no weights" tab provides a cleaner, more informative view for better understanding.
An exciting aspect of this tool is the opportunity to experiment with the architecture through interactive elements, such as altering parameters and observing their effects on the processed data. This hands-on approach significantly aids in visualizing the mechanics of transformers.
Usage Instructions
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Understand that every block in the spreadsheet represents values or parameters processed through the GPT architecture. The color coding is as follows:
- Purple: Replace with parameters from a trained model.
- Green: Values transformed from input to output stages.
- Orange: Intermediate calculations for clarity.
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The processing path starts from the top of the spreadsheet and flows to the bottom. Users will encounter labeled sections correlating to different stages of processing across three transformers (labeled 0, 1, and 2).
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An Excel version has been added, featuring a "MAP" tab and a "Visual Structure of the pipeline" tab to aid navigation, although multiple tables cannot be displayed on one page due to Excel's limitations.
Potential Uses
- Develop a visual understanding of transformer architecture.
- Explore actual calculations within each cell by double-clicking to view function details.
- Identify interactions by selecting green value cells to view influences.
- Modify parameters to observe changes in output.
- Utilize weights from NanoGPT to replace spreadsheet parameters for accurate results.
Collaborative Opportunities
The project invites contributions, encouraging individuals interested in more advanced setups beyond nanoGPT. The shared knowledge could further expand this innovative approach to comprehending machine learning models.
Acknowledgments
This project draws inspiration and knowledge from several influential resources, including:
- Andrej Karpathy's YouTube tutorial and NanoGPT project.
- Brendan Bycroft's 3D transformer visualization project.
- 3Blue1Brown's LLM course on YouTube.
For those intrigued by the potential of integrating GPT pipelines in spreadsheets, these references offer valuable insights far exceeding the scope of "spreadsheet is all you need".