Skip to main content

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. All converters are tested with onnxruntime.

Documentation

Full documentation including tutorials is available at https://onnx.ai/sklearn-onnx/. Supported scikit-learn Models Last supported opset is 15.

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

Contribute

We welcome contributions in the form of feedback, ideas, or code.

License

Apache License v2.0

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

skl2onnx-1.11.tar.gz (859.7 kB view details)

Uploaded Source

Built Distribution

skl2onnx-1.11-py2.py3-none-any.whl (274.5 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file skl2onnx-1.11.tar.gz.

File metadata

  • Download URL: skl2onnx-1.11.tar.gz
  • Upload date:
  • Size: 859.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.6.0 importlib_metadata/4.6.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.9.5

File hashes

Hashes for skl2onnx-1.11.tar.gz
Algorithm Hash digest
SHA256 7067deb0430c03d6843d113b760320a8fd13ba926ff0a5329c2081dfbce85ec5
MD5 2f2556be4495265b6d4aa0da219b42a0
BLAKE2b-256 27602d9f11565e7b44cd6b844f829af53a1cd3ef6332a7a65231cc028c1af9ce

See more details on using hashes here.

File details

Details for the file skl2onnx-1.11-py2.py3-none-any.whl.

File metadata

  • Download URL: skl2onnx-1.11-py2.py3-none-any.whl
  • Upload date:
  • Size: 274.5 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.6.0 importlib_metadata/4.6.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.1 CPython/3.9.5

File hashes

Hashes for skl2onnx-1.11-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 3942a97f30fc0c8d2fb4d715332714a3f0571f33b8075f4aa3b2b234566165c4
MD5 8a8b8f9f48f8b9196cd551a528d0496c
BLAKE2b-256 4cbf48210428aca59bcefa94ff52f12981f07be13809441754ed86c1abe43d1c

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page