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array programming
compilers
jax computing machinery
jax-related libraries and projectsllm
lm stuff emphasizing compute (scale, chips, etc.)misc
other starsscientific
engineering and the sciences; optimization and numerical stuffsequential
sequential simulation, modeling, and predictionStars
Language: Python
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Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
A high-throughput and memory-efficient inference and serving engine for LLMs
DSPy: The framework for programming—not prompting—foundation models
Open source code for AlphaFold.
Flax is a neural network library for JAX that is designed for flexibility.
SGLang is yet another fast serving framework for large language models and vision language models.
Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
Large language models (LLMs) made easy, EasyLM is a one stop solution for pre-training, finetuning, evaluating and serving LLMs in JAX/Flax.
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
A JAX research toolkit for building, editing, and visualizing neural networks.
Optax is a gradient processing and optimization library for JAX.
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
A Python-level JIT compiler designed to make unmodified PyTorch programs faster.
Hardware accelerated, batchable and differentiable optimizers in JAX.
BlackJAX is a Bayesian Inference library designed for ease of use, speed and modularity.
An implementation of the Fermionic Neural Network for ab-initio electronic structure calculations
Legible, Scalable, Reproducible Foundation Models with Named Tensors and Jax
PIX is an image processing library in JAX, for JAX.