#
Installation

> `kernels` has not reached `1.0` yet. Until then, minor releases may contain breaking changes. If you depend on `kernels` in a library or application, we strongly recommend pinning a version range rather than an unbounded dependency. For example, in `pyproject.toml`:

>     dependencies = [
>         "kernels>=0.15,<0.16",
>     ]

> or equivalently `kernels~=0.15` (compatible release). This protects your project from unexpected breakage when a new `kernels` version is released.

Install the `kernels` package with `pip` (requires `torch>=2.5` and CUDA):

    pip install kernels

or with `uv`

    uv pip install kernels

or if you want the latest version from the `main` branch:

    pip install "kernels[benchmark] @ git+https://github.com/huggingface/kernels#subdirectory=kernels"

> On Windows, we recommend using the Linux version of Torch through WSL 2, since many more kernels support Linux. If you want to use GPU acceleration, check out the CUDA on WSL and PyTorch with DirectML on WSL 2 guides.

> We strongly recommend not using a free-threaded Python build yet. These builds are not only experimental, but do not support the stable ABI on Python versions before 3.15. Kernels are compiled with the stable ABI to support a wide range of Python versions.

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