sac-n-jax

Python code for "Probabilistic Machine learning" book by Kevin Murphy

Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023

Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.

Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/

Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/

High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC

From the Tensor to Stable Diffusion, a rough outline for a 1 week course.

Long Range Arena for Benchmarking Efficient Transformers

The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.