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jax authors 2024-12-10 06:00:05 -08:00
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@ -253,18 +253,14 @@ simply run:
conda install jax -c conda-forge
```
To install it on a machine with an NVIDIA GPU, run:
If you run this command on machine with an NVIDIA GPU, this should install a CUDA-enabled package of `jaxlib`.
To ensure that the jax version you are installing is indeed CUDA-enabled, run:
```bash
conda install "jaxlib=*=*cuda*" jax cuda-nvcc -c conda-forge -c nvidia
conda install "jaxlib=*=*cuda*" jax -c conda-forge
```
Note the `cudatoolkit` distributed by `conda-forge` is missing `ptxas`, which
JAX requires. You must therefore either install the `cuda-nvcc` package from
the `nvidia` channel, or install CUDA on your machine separately so that `ptxas`
is in your path. The channel order above is important (`conda-forge` before
`nvidia`).
If you would like to override which release of CUDA is used by JAX, or to
install the CUDA build on a machine without GPUs, follow the instructions in the
[Tips & tricks](https://conda-forge.org/docs/user/tipsandtricks.html#installing-cuda-enabled-packages-like-tensorflow-and-pytorch)