onnx and onnxmltools

ONNXMLTools is a conversion utility that transforms machine learning models from various frameworks into the ONNX format defined by the core ONNX specification, making them complements that are used together in a conversion pipeline.

onnx
85
Verified
onnxmltools
73
Verified
Maintenance 20/25
Adoption 15/25
Maturity 25/25
Community 25/25
Maintenance 10/25
Adoption 14/25
Maturity 25/25
Community 24/25
Stars: 20,477
Forks: 3,896
Downloads:
Commits (30d): 43
Language: Python
License: Apache-2.0
Stars: 1,143
Forks: 214
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
No risk flags
No risk flags

About onnx

onnx/onnx

Open standard for machine learning interoperability

This project offers an open-source format for AI models, helping AI developers use different machine learning tools interchangeably. It takes an AI model trained in one framework and converts it into a standardized format, allowing it to be used (especially for scoring/inferencing) in another framework or hardware. AI developers who build and deploy machine learning models are the primary users.

AI model deployment machine learning interoperability model inference deep learning AI development

About onnxmltools

onnx/onnxmltools

ONNXMLTools enables conversion of models to ONNX

This tool helps machine learning engineers and data scientists convert their trained models from various frameworks like scikit-learn, TensorFlow, or Core ML into the ONNX format. You provide a model trained in one of the supported toolkits, and it outputs an equivalent model in the ONNX standard format. This allows for easier deployment and portability across different inference runtimes and hardware.

machine-learning-operations model-deployment data-science-workflow AI-engineering predictive-analytics

Scores updated daily from GitHub, PyPI, and npm data. How scores work