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.
