Convert scikit-learn models to ONNX
Project description
## Introduction sklearn-onnx converts [scikit-learn](https://scikit-learn.org/stable/) models to [ONNX](https://github.com/onnx/onnx). Once in the ONNX format, you can use tools like [ONNX Runtime](https://github.com/Microsoft/onnxruntime) for high performance scoring.
## Documentation Full documentation including tutorials is available at [http://onnx.ai/sklearn-onnx/](http://onnx.ai/sklearn-onnx/).
You may also find answers in [existing issues](https://github.com/onnx/sklearn-onnx/issues?utf8=%E2%9C%93&q=is%3Aissue) or submit a new one.
## Installation You can install from [PyPi](https://pypi-hypernode.com/project/skl2onnx/): ` 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 sklearn-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 [MIT License](LICENSE)
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
File details
Details for the file skl2onnx-1.4.4.tar.gz.
File metadata
- Download URL: skl2onnx-1.4.4.tar.gz
- Upload date:
- Size: 522.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: Python-urllib/3.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 231ab3253d91d6b3becfb7b641199eee35eadcd21d2b3c4bb700e8a686630c2f |
|
| MD5 | 4a70f9f7e4387d86bb478819b523a731 |
|
| BLAKE2b-256 | 3e2dd0b789618449b62d1af50e40924c57cd16449e4197b73543bded0fc27d80 |
