{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/2"}],"enrichment":{"capability":"Converts trained scikit-learn models to ONNX format for deployment and high-performance inference using ONNX Runtime or other compatible tools.","skillfed_tags":["model-export","ml-deployment","inference-optimization"],"use_cases":["Deploy scikit-learn models to production systems using ONNX Runtime.","Convert scikit-learn pipelines to a portable format that can run on different platforms or languages via ONNX.","Integrate scikit-learn models into applications that require ONNX format for compatibility with existing inference infrastructure.","Export trained models for use in edge devices or resource-constrained environments where ONNX Runtime is available.","Register external converters to extend ONNX support for models or transformers from external libraries."],"what_it_does":"skl2onnx is a converter that takes trained scikit-learn models and transforms them into ONNX (Open Neural Network Exchange) format, an open standard for representing machine learning models. Once converted, models can be deployed and executed using ONNX Runtime or other ONNX-compatible inference engines. The package handles scikit-learn pipelines, individual models, and transformers, with support for external converters to extend functionality. It supports opset 21 and has been tested against onnxruntime.\n\nThe conversion workflow is straightforward: train a scikit-learn model, call to_onnx() with a sample input, serialize the result, and load it into an inference runtime. This is useful for deploying models in production environments where portability or interoperability with other ML frameworks matter.","worth_installing":"Yes. The package is actively maintained, has no known vulnerabilities, installs with minimal friction, and solves a real deployment problem\u2014getting scikit-learn models into a portable format. Use it if you need to deploy scikit-learn models outside their native environment."},"id":"skl2onnx","links":{"html":"https://skillfed.io/packages/skl2onnx","md":"https://skillfed.io/packages/skl2onnx.md","pypi":"https://pypi.org/project/skl2onnx/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-01-30","license_spdx":null,"license_treatment":"permissive","name":"skl2onnx","python_support":"supports_current","summary":"Convert scikit-learn models to ONNX"},"popularity":{"monthly_downloads":2556584,"position":3002,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.20.0"}