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A Python library for composable transformations of numerical programs: automatic differentiation, vectorization, and JIT compilation to GPU/TPU.
A Python library for composable transformations of numerical programs: automatic differentiation, vectorization, and JIT compilation to GPU/TPU.
A Python library for accelerator-oriented array computation and program transformation, designed for high-performance numerical computing and machine learning.
A fast, differentiable physics engine built with JAX for massively parallel rigid body simulation on accelerator hardware.
A JAX/Flax-based framework for easy and scalable pre-training, fine-tuning, evaluation, and serving of large language models.
A language for distributed deep learning that simplifies model parallelism by specifying tensor computations across hardware meshes.
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