The most intuitive explanation of how AI models like GPT, Claude, and Gemini actually work.
A beautiful interactive guide explaining the Transformer architecture — the technology behind modern AI.
No prior ML knowledge required.
Open directly in your browser:
index.html
or host on GitHub Pages
✔ What Transformers are
✔ Tokenization (Text → Numbers)
✔ Embeddings (Words as vectors)
✔ Self Attention explained visually
✔ Query / Key / Value mechanism
✔ Multi-Head Attention
✔ Full Transformer Architecture
✔ GPT vs Claude vs Gemini comparison
✔ Context Windows
✔ Model Training
✔ Quantization
✔ AI Agents
✔ Function Calling
✔ Voice Models (TTS)
✔ Image Generation
✔ Video Generation
Everything explained from beginner → expert level.
Most explanations of Transformers are:
• Too mathematical
• Too abstract
• Too academic
This guide focuses on clear visuals + intuitive explanations.
Pure HTML + CSS
No frameworks.
No dependencies.
Just open the file.
Clone the repo:
git clone https://github.com/Harsha-hue/visual-transformer-guideOpen:
index.html
• AI beginners
• Developers learning LLMs
• Students
• ML engineers
• Anyone curious about ChatGPT
If you found this helpful:
⭐ Star the repo
🍴 Fork it
📢 Share it
MIT License
Use freely for learning or projects.
Pull requests welcome.
Ideas for improvements:
• Add interactive attention demos
• Add PyTorch implementation
• Add animated diagrams
Created to make AI understandable for everyone.
@Harsha-hue