rti/gptvis

Understanding Transformers Using A Minimal Example

32
/ 100
Emerging

This project helps machine learning engineers and researchers understand how Transformer Large Language Models work internally. It takes a simplified Transformer model and a small dataset as input, then visualizes the model's internal states, showing how information flows and how the attention mechanism operates. This allows a detailed, step-by-step observation of the core processes, making complex concepts tangible.

No commits in the last 6 months.

Use this if you are a machine learning engineer or researcher struggling to form a mental model of Transformer LLMs due to the vast number of internal parameters.

Not ideal if you are looking for a tool to develop or deploy large-scale LLMs, as this focuses purely on explaining simplified model mechanics.

Large Language Models Transformer architecture Deep Learning interpretability Neural Network visualization AI research
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 8 / 25
Maturity 15 / 25
Community 7 / 25

How are scores calculated?

Stars

52

Forks

3

Language

Python

License

MIT

Last pushed

May 05, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/transformers/rti/gptvis"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.