Transformer Math Explorer [P]

Reddit r/MachineLearning Tools

Summary

This interactive tool visualizes the mathematical underpinnings of transformer models through dataflow graphs, covering architectures from GPT-2 to Qwen 3.6 and various attention mechanisms.

This is an interactive math reference for transformer models, presented via dataflow graphs, all the way down to elementary math. Covers models from GPT-2 to Qwen 3.6, with MLA, MoE, RoPE, MTP, hybrid attention, and other variants toggleable. Originally made this for myself to keep track of all the variations. If you find errors or find something unintuitive or misleading let me know!
Original Article

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@currying: Very nice 13-page exposition!

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A tweet highlights 'Understanding Transformers and Attention Mechanisms,' a 13-page paper that explains the Transformer architecture and attention from an applied mathematics perspective.