# aburkov/theLMbook

This is the official repository for The Hundred-Page Language Models Book by Andriy Burkov

Repository: https://github.com/aburkov/theLMbook
Canonical: https://ross.abutalabs.com/products/thelmbook
Homepage: https://www.thelmbook.com
Language: Jupyter Notebook
License Family: other
Last push: 2026-02-08T21:14:56+00:00

## Health v2 (maintenance only)
Score: 44/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 66, release rhythm 8, longevity 56
- inputs: {"age_days": 796, "days_push": 206, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2179, forks 368 (observed 2026-08-28T04:06:23.048922+00:00)

## What it is
The official companion repository for The Hundred-Page Language Models Book by Andriy Burkov, containing complete Python/PyTorch implementations and Jupyter notebooks for each chapter. It teaches language models step by step, from count-based methods through RNNs to modern transformers and LLM finetuning.

## Use cases
- learn how large language models work from scratch
- implement language models in PyTorch with guided notebooks
- study the math behind transformers and RNNs
- learn prompt engineering and LLM finetuning
- progress from machine learning basics to modern LLM architectures
- find hands-on code examples for a language models book

## When to choose
- you want a concise, math-grounded introduction to language models with runnable code
- you prefer building understanding incrementally from simple models to transformers
- you are a developer, data scientist, or ML engineer new to LLMs

## When to avoid
- you need a production-ready LLM library or framework rather than educational material
- you want exhaustive, state-of-the-art coverage beyond a hundred-page treatment
- you need a licensed, reusable codebase - the repo has no license

## Facets
- artifact type: learning-resource
- maturity: active
- function: machine-learning, deep-learning, llm-training, prompt-engineering, nlp
- domain: large-language-models, machine-learning, deep-learning, tutorials, education
- platform: python
- tags: book, jupyter-notebooks, pytorch, language-models, educational, companion-code, natural-language-processing

## Member repositories
- aburkov/theLMbook (main) score 44

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:23.048922+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:48:45.506884+00:00, confidence not recorded.
  - readme: https://github.com/aburkov/theLMbook (fetched 2026-08-28T04:06:23.048922+00:00, sha 61ec9d9274ad)
  - homepage: https://www.thelmbook.com (fetched 2026-08-29T10:28:41.765165+00:00, sha 6e721100f548)
- Data as of 2026-08-30T08:39:29.467469+00:00.