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Curated list of the best truly open-source AI projects, models, tools, and infrastructure. Daily updated.
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Deep Learning for humans
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
Flax is a neural network library for JAX that is designed for flexibility.
A retargetable MLIR-based machine learning compiler and runtime toolkit.
JAX-based neural network library
Elegant easy-to-use neural networks + scientific computing in JAX. https://docs.kidger.site/equinox/
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
Automated Machine Learning on Kubernetes
Modular Reinforcement Learning (RL) library (implemented in PyTorch, JAX, and NVIDIA Warp) with support for Gymnasium/Gym, NVIDIA Isaac Lab, MuJoCo Playground and other environments