I built a tool that shows you what GPT-2 is "thinking" in real-time as it generates 3D graph of concept activations per token [R]

In three linesAXON visualizes real-time concept activations in GPT-2 through a 3D force-directed graph. A Sparse Autoencoder decomposes the residual stream into interpretable features (geography, cities, languages) per generated token. Stack: TransformerLens + SAELens (backend), FastAPI WebSocket, Three.js (frontend). ~35ms/token on GPU.

Summary generated by Claude — human-verified