Convert scikit-learn models to ONNX
Project description
Introduction
sklearn-onnx converts scikit-learn models to ONNX. Once in the ONNX format, you can use tools like ONNX Runtime for high performance scoring.
Documentation
Full documentation including tutorials is available at https://onnx.ai/sklearn-onnx/.
You may also find answers in existing issues or submit a new one.
Installation
You can install from PyPi:
pip install skl2onnx
Or you can install from the source with the latest changes.
pip install git+https://github.com/onnx/sklearn-onnx.git
If you install onnx from its source code, you must set the environment variable ONNX_ML=1
before installing the onnx package.
Contribute
We welcome contributions in the form of feedback, ideas, or code.
License
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
skl2onnx-1.9.2.tar.gz
(757.4 kB
view hashes)
Built Distribution
skl2onnx-1.9.2-py2.py3-none-any.whl
(240.9 kB
view hashes)
Close
Hashes for skl2onnx-1.9.2-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | fea1d2e13541f4703bb3f414c8f91be7102a2dc1d6cfd687f3e9f0ff5c093c2c |
|
MD5 | d23cee2f77e32019100a4afb8d82b5ac |
|
BLAKE2b-256 | fb3d6c8f1f1499f38b172810e44f62eddf1c3effc90be7899cfaa8a7657bf980 |