jax-ml/scaling-book

A simple, performant, and scalable Jax LLM!

A Practitioner handbook for production llm serving.

Everything you need to know about LLM inference

LLM notes, including model inference, transformer model structure, and llm framework code analysis notes.

Deep learning for dummies. All the practical details and useful utilities that go into working with real models.

Recipes to scale inference-time compute of open models

Source code repo for book: Hands-On LLM Serving and Optimization: Hosting LLMs at Scale

Modalities, a PyTorch-native framework for distributed and reproducible foundation model training.

100 days of LLM inference engineering — daily posts, experiments, and visualizations