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Learn AI Engineering! Learn it. Build it. Ship it for others.

This repository contains the code for developing, pretraining, and finetuning a GPT-like LLM and is the official code repository for the book Build a Large Language Model (From Scratch).

Implementing LLM architectures from scratch in PyTorch

Build a modern LLM from scratch. Every line commented. Explained like we are five.

Most people learn ML frameworks by importing them. We built ours by hand, then made it hit harder.

24 GB of RAM. Portable C99: no BLAS, no framework, no GPU.

Official SGLang x Datawhale course on LLM inference: understand inference, build a mini-sglang from scratch, then read the real SGLang source and land your first PR. Available in English and Chinese.

The purpose of this project is not to produce as optimized and computationally efficient algorithms as possible but rather to present the inner workings of them in a transparent and accessible way.

until forever. Exceptional understanding of French with the flawless accent implies correct exposure to exceptional French and flawless accent. Similarly, great AI Researchers & engineers with excellent problem-skills imply quality knowledge consumed and exposure rich experience.

Learn to build AI agents locally without frameworks. Understand what happens under the hood before using production frameworks.

SerenityOS is a love letter to '90s user interfaces with a custom Unix-like core. It flatters with sincerity by stealing beautiful ideas from various other systems.

mini-AGI - is a continual learning byte-level language model that assembles its own architecture, trains from scratch on a single 8 GB VRAM GPU, and keeps learning from everything it reads.

c). You might think that you need many billion parameter LLMs to do anything useful, but in fact very small LLMs can have surprisingly strong performance if you make the domain narrow enough (ref: TinyStories paper).

This repository contains a step-by-step guide that teaches how to create a simple operating system (OS) kernel from scratch. I call this OS Raspberry Pi OS or just RPi OS.

:zap:机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归

Am I missing your favorite model? Is there something that could be cleaner / less confusing? Did I mess something up?

also, im going to load tensors directly from the model file that meta provided for llama3, you need to download the weights before running this file. here is the offical link to download the weights:

C in four functions

View rendered tutorial (with more details on what this is.)

PyTorch implementations of modern open-source LLM architectures (Llama, Qwen, DeepSeek, Gemma, GPT-OSS, Kimi, and more) — written from scratch for readability and learning, based on Sebastian Raschka's LLM Architecture Gallery.

lytlnyblOS (little nibble OS) is a small, from scratch 32-bit operating system that comes with a complete guide book to teach beginners practically about OS development.