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WangNet – 1.8 MB, zero-dependency Numberwang adjudication in 11 languages

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Why This Matters

This project is a lighthearted parody rather than a serious tool, but it highlights a broader trend of developers building tiny, dependency-free neural network models that can run anywhere without heavy ML frameworks. It's a fun demonstration of how far minimalist, zero-install AI inference can go, even for absurdist tasks referencing a comedy sketch.

Key Takeaways

Numberwang

A small neural network that decides whether a number is Numberwang.

The whole model is a 1.8 MB JSON file and the inference code is about 100 lines of pure Python standard library — no PyTorch, no NumPy, nothing to install. Clone it and run it.

$ python3 numberwang.py 22 22... THAT'S NUMBERWANG! (confidence: 99.3%) $ python3 numberwang.py " 45 - 44 " 45 - 44... That's Wangernumb! Rotate the board! (confidence: 100.0%) $ python3 numberwang.py " hello how are you " hello how are you... That's not even a number. It can never be Numberwang. (confidence: 100.0%)

Usage

git clone https://github.com/GraafHenk/numberwang cd numberwang python3 numberwang.py 22

Run it with no arguments for an interactive session:

$ python3 numberwang.py Welcome to Numberwang! (ctrl-c to stop playing Numberwang) > zweiundzwanzig zweiundzwanzig... THAT'S NUMBERWANG! (confidence: 100.0%) > shinty-six shinty-six... That's not Numberwang. (confidence: 100.0%)

Requires Python 3.8 or newer. That's the only requirement.

In your own code

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