Installation

FHElium builds its native extension against the PyTorch installation in the active environment. Use Python 3.12 or 3.13, install the intended PyTorch distribution from the official PyTorch selector, and provide a C++17-capable compiler.

Install FHElium

Operating system

Package method

Torch version

Compute platform

python -m pip install --index-url https://download.pytorch.org/whl/cu130 "torch==2.13.0+cu130"
python -m pip install "scikit-build-core>=1.0.3" "cmake>=3.18" ninja
CMAKE_ARGS="-DFHELIUM_NATIVE_BACKENDS=CPU+CUDA"   python -m pip install --no-binary=fhelium     --no-build-isolation --no-cache-dir --verbose "fhelium==0.10.0"

FHElium is under active development. APIs may change significantly between releases.

Binary compatibility includes the Python ABI, exact Torch version, Torch CUDA version, C++ ABI, and compiled GPU architectures. Prebuilt Linux wheels are complete fhelium wheels served by FHElium's static release store. The installer above selects the configuration-specific wheel index corresponding to the chosen Torch and compute platform. PyPI provides the source distribution for supported source-build environments.

The following command builds from the PyPI source distribution against the preinstalled target Torch environment:

python -m pip install "scikit-build-core>=1.0.3" "cmake>=3.18" ninja
CMAKE_ARGS="-DFHELIUM_NATIVE_BACKENDS=CPU+CUDA" \
  python -m pip install \
    --no-binary=fhelium \
    --no-build-isolation --no-cache-dir --verbose \
    fhelium

CUDA source builds require a toolkit with the same major version as the preinstalled Torch CUDA build; using the same minor version is preferred. CPU-only builds set CMAKE_ARGS="-DFHELIUM_NATIVE_BACKENDS=CPU". CMAKE_CUDA_ARCHITECTURES optionally overrides the generated architecture list.

Verify

python -c "import torch, fhelium; print(torch.__version__, fhelium.__version__)"
python -c "from fhelium.native import native_status; print(native_status())"

For a CUDA build, inspect visible devices with fhelium cuda info. If the selected Torch, CUDA, compiler, or cached native binary is incompatible, native_status() reports the detected build metadata and a targeted rebuild instruction.