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
2 maintainers
Metadata
2 maintainers
Release files for skl2onnx 1.13
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| skl2onnx-1.13.tar.gz | 872.6 kB | Without provenance | Details for skl2onnx-1.13.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| skl2onnx-1.13-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details for skl2onnx-1.13-py2.py3-none-any.whl |
Total release size: 1.2 MB
Release files / skl2onnx-1.13.tar.gz
| Download URL | skl2onnx-1.13.tar.gz |
|---|---|
| Size | 872.6 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / skl2onnx-1.13-py2.py3-none-any.whl
| Download URL | skl2onnx-1.13-py2.py3-none-any.whl |
|---|---|
| Size | 288.7 kB |
| Tags | Python 2 Python 3 |
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twine/3.8.0 pkginfo/1.8.2 readme-renderer/30.0 requests/2.26.0 requests-toolbelt/0.9.1 urllib3/1.26.7 tqdm/4.62.3 importlib-metadata/4.11.2 keyring/23.2.1 rfc3986/1.5.0 colorama/0.4.4 CPython/3.9.7
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Security for skl2onnx 1.13
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