# naklecha/llama3-from-scratch

llama3 implementation one matrix multiplication at a time

Repository: https://github.com/naklecha/llama3-from-scratch
Canonical: https://ross.abutalabs.com/products/llama3-from-scratch
Language: Jupyter Notebook
License: MIT
License Family: permissive
Last push: 2024-05-23T14:34:05+00:00

## Health v2 (maintenance only)
Score: 24/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 59
- inputs: {"age_days": 836, "days_push": 832, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 15222, forks 1279 (observed 2026-08-28T04:11:09.403583+00:00)

## What it is
A Jupyter Notebook that implements the Llama 3 language model from scratch, building each tensor and matrix multiplication step by step while loading Meta's official model weights directly. It serves as an educational walkthrough of transformer internals including tokenization, attention, and feed-forward layers.

## Use cases
- understand how llama3 works internally
- learn transformer architecture from scratch
- implement attention and matrix multiplications manually
- study how model weights are loaded from checkpoint files
- teach large language model fundamentals
- follow along a hands-on LLM implementation tutorial

## When to choose
- you want to deeply understand LLM internals rather than just call an API
- you are learning how transformers and attention work at the tensor level
- you want a readable, step-by-step educational notebook with real Meta weights

## When to avoid
- you need a production-ready inference engine with optimized performance
- you want a maintained library with releases and support
- you need training or fine-tuning capabilities rather than inference walkthrough

## Facets
- artifact type: learning-resource
- maturity: stable
- function: llm-inference, deep-learning, machine-learning
- domain: large-language-models, deep-learning, tutorials, artificial-intelligence
- platform: python
- tags: llama3, transformers, from-scratch, notebook, tutorial, attention, tokenizer, education

## Member repositories
- naklecha/llama3-from-scratch (main) score 24

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:09.403583+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 2026-08-29T17:06:33.029808+00:00, confidence not recorded.
  - readme: https://github.com/naklecha/llama3-from-scratch (fetched 2026-08-28T04:11:09.403583+00:00, sha 4bb255271a77)
- Data as of 2026-08-30T08:39:29.467469+00:00.