# karpathy/LLM101n

LLM101n: Let's build a Storyteller

Repository: https://github.com/karpathy/LLM101n
Canonical: https://ross.abutalabs.com/products/llm101n
License Family: other
Archived: true
Last push: 2024-08-01T01:20:33+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 59
- inputs: {"age_days": 829, "days_push": 763, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 37505, forks 2078 (observed 2026-08-28T04:12:01.432557+00:00)

## What it is
LLM101n is a planned course by Andrej Karpathy and Eureka Labs that teaches building a Storyteller AI large language model end-to-end, from basics to a ChatGPT-like web app, in Python, C, and CUDA. The repository currently only contains a syllabus and is archived while the course is under development.

## Use cases
- learn how large language models work from scratch
- build a GPT-style transformer step by step
- understand backpropagation and training optimization
- learn tokenization, kv-cache, and quantization
- study finetuning techniques like SFT, LoRA, RLHF, and DPO
- learn to deploy an LLM as a web app

## When to choose
- you want a structured, fundamentals-first path to understanding LLMs and deep learning
- you prefer building everything from scratch rather than using high-level frameworks
- you want to follow Karpathy's teaching style after enjoying nanoGPT or Zero To Hero

## When to avoid
- you need a ready-to-use course today - it does not yet exist and the repo is archived
- you want production LLM tooling rather than educational material
- you need a license-cleared codebase to reuse - no license is specified

## Facets
- artifact type: learning-resource
- maturity: experimental
- function: machine-learning, deep-learning, llm-training, llm-inference
- domain: large-language-models, deep-learning, machine-learning, education, tutorials
- platform: python, cpp, cross-platform
- tags: course, llm-from-scratch, storyteller, transformers, archived, eureka-labs, syllabus, education, gpu

## Member repositories
- karpathy/LLM101n (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:01.432557+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 2026-08-29T16:25:38.058692+00:00, confidence not recorded.
  - readme: https://github.com/karpathy/LLM101n (fetched 2026-08-28T04:12:01.432557+00:00, sha b5a007cabdc2)
- Data as of 2026-08-30T08:39:29.467469+00:00.