ML Without Magic: Building a Tiny Language Model in Pure Node.js and Watching Every Weight Change

Tokenization → embeddings → causal Transformer → LM head → softmax → loss → backpropagation. No TensorFlow, no PyTorch, and no hidden autograd.

Repository: tiny-language-model-neuro-js.

Most explanations of language models present correct formulas but hide the path between them inside a framework. I wanted the opposite: one small scenario where every scalar is visible and where the terminal clearly shows incorrect answers before learning and correct answers after it.

The project now has one command:

node src/train.js --generalize --adaptive-teach