model-optimization
Toolkit for optimizing ML models in Keras and TensorFlow
GraphCanon updated 3w · GitHub synced 3w
Decision brief
Toolkit for optimizing ML models in Keras and TensorFlow, focusing on quantization and pruning.
Good fit when
- When you are working with Keras or TensorFlow models and need to apply post-training quantization or pruning techniques to minimize model size and enhance inference speed.
- If your project requires compression that is explicitly supported by the toolkit for better performance on edge devices.
Avoid when
- Do not use this toolkit if you are working with ML models outside of Keras and TensorFlow frameworks, as it does not support other popular frameworks like PyTorch.
- Avoid using this toolkit when detailed customization is needed beyond its quantization and pruning options, since the available methods might be too limited for complex optimization tasks.
Observed Jul 16, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Active (8d since push)
- As of 3w
- Provenance
- Not a fork · Organization account
- As of 3w
- Security (OSV)
- No criticals
- As of 1mo
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Install
pip install model-optimizationHow it fits your stack(2)
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Evidence and technical details
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Overview
Provides functionalities including quantization and pruning to optimize models for deployment.
Capability facts
- Languages
- python
Source: github.language · Aug 4, 2026
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README
Installation
For installation instructions, see tensorflow.org/model_optimization/guide/install.
For agents
This page has a .md twin and JSON over the API.