Interactive 3D LLM Engine
3D LLM Visualization
Explore how GPT Transformer models process tokens, calculate self-attention, project query/key/value vectors, and compute next-token probability distributions step-by-step.
Direct Answer: How does the 3D LLM Visualizer work?
The 3D LLM Visualizer is an interactive WebGL engine that renders the internal layer-by-layer forward pass of a GPT Transformer. Step inside the neural network to inspect token embedding lookups, multi-head self-attention QKV vector matrix math (Softmax(QK^T / sqrt(d_k))V), GELU feedforward expansions, layer norm, and output logit probabilities.