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Building a 200M parameter LLM from scratch in PyTorch

This story is from 2026-09-03. It is preserved in the archive; the latest stories are on the live feed.

It's really easy to spin up Unsloth and fine-tune Llama 3 in an afternoon. I wanted to see what happens when you don't do that. I wanted to write the BPE tokenizer, implement RoPE, code the SwiGLU feed-forward blocks, and write the training loop in pure PyTorch from absolute scratch. The result is…

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  1. 2026-09-03 09:20 · DEV Community — Machine Learning
    Building a 200M parameter LLM from scratch in PyTorch

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