Scaling up and the PyTorch mapping
What changes between a 4k-parameter toy and a real LLM: scaling laws and compute budgets (6ND, tokens per parameter), data pipelines, mixed precision, parallelism, checkpoints and evaluation, plus a compact PyTorch GPT showing how each piece of your pure-Python model maps to tensors.
18 min·Verified 2026-111 animated diagramPro+50 XP
You have built every algorithmic piece of a language model. Scaling it is mostly engineering plus a handful of principles about where to spend compute.
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