PulseAugur
EN
LIVE 17:11:09

Build a GPT from scratch with NumPy: 34-chapter tutorial released

By PulseAugur Editorial · [1 sources] ·

A new 34-chapter tutorial, available for free, guides readers through building a generative pre-trained transformer (GPT) from scratch using only NumPy. The tutorial begins with fundamental neural network concepts and progresses to advanced LLM topics like attention mechanisms, pre-training, and various sampling strategies. Designed for self-learners and engineers seeking a deeper understanding of LLM internals, the entire book can be trained on a laptop's CPU without requiring a GPU. AI

IMPACT Provides a foundational understanding of LLM architecture and training for developers without relying on high-level frameworks.

RANK_REASON The item describes a detailed tutorial and accompanying code for building a GPT from scratch using NumPy, functioning as an educational resource and a reference implementation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Build a GPT from scratch with NumPy: 34-chapter tutorial released

How we ranked this

Signal score
42 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
The item describes a detailed tutorial and accompanying code for building a GPT from scratch using NumPy, functioning as an educational resource and a reference implementation. [lever_c_demoted fro…
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
paper, other
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

Full methodology in our editorial standards.

COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Steven Li ·

    I built a GPT from scratch in NumPy only – 34 notebooks, no PyTorch

    <p>I wanted to understand LLMs below the framework level, so I wrote a 34-chapter tutorial that starts from a single neuron and builds up to a ~10.8M-parameter GPT — tensors, computational graphs, autograd, attention, pre-training, sampling, KV cache, SFT and DPO — using nothing …

RELATED ENTITIES

RELATED TOPICS