uni-quant-cuda 0.2.0

Uni-Quant: CUDA-accelerated quantization/dequantization for Keras and XGBoost models

Uni-Quant

Small library to quantize/dequantize Keras and XGBoost models using PyTorch CUDA kernels.

Notes

• This package compiles CUDA kernels at runtime using torch.utils.cpp_extension.load_inline.
• Installing and using the CUDA compilation requires a compatible PyTorch build and CUDA toolkit on the target machine.

Dependencies are listed in requirements.txt and synchronized with pyproject.toml.

Quick publish test

Build a source/wheel and check locally:

python -m pip install --upgrade build twine
python -m build
python -m twine check dist/*

Upload (example):

python -m twine upload dist/*