less than 650 LOC trainable GPT only using NumPy

In plain words

This is a trainable GPT implementation written in fewer than 650 lines of code using only NumPy. It is designed for developers and machine learning enthusiasts who want to understand or build GPT models from scratch without relying on large frameworks. The project stands out for its minimal dependency footprint and compact codebase, making it useful for education, experimentation, or creating lightweight language model implementations.

written from the facts on this page · September 2026

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