Metadata-Version: 2.4
Name: uni-quant-cuda
Version: 0.2.1
Summary: Uni-Quant: CUDA-accelerated quantization/dequantization for Keras and XGBoost models
Author-email: Jakub Grula <ramsters110@gmail.com>
License: MIT
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: POSIX :: Linux
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: license-file

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 CUDA toolkit on the target machine. (Tested with 13.1)
