KerasTuner searches hyperparameters to optimize machine learning models built with Keras.
Open source
24 alternativesTensorFlow Model Optimization
TensorFlow Model Optimization provides Keras and TensorFlow tools for model quantization and pruning.
About TensorFlow Model Optimization
TensorFlow Model Optimization is an open source toolkit for optimizing machine learning models for deployment and execution. It is built for Keras and TensorFlow and provides quantization and pruning for sparse weights. According to the project's homepage, it is intended for both novice and advanced users.
The toolkit includes APIs designed specifically for Keras and provides stable Python APIs. Installation instructions, tutorials, and API documentation are published on tensorflow.org/model_optimization. The project is licensed under Apache-2.0. Pricing is unknown.
Key features
- Quantization and pruning for sparse weights
- APIs built specifically for Keras
- Stable Python APIs
- Subpackages for clustering, quantization, and sparsity
Best for: Machine learning developers who use Keras or TensorFlow and want to optimize models for deployment and execution.
Good for
- Provides stable Python APIs
- Released as open source under the Apache-2.0 license
- Includes tutorials and API documentation on tensorflow.org
TensorFlow Model Optimization at a glance
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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TensorFlow Model Optimization FAQ
Where can I find installation instructions?
Installation instructions are available at tensorflow.org/model_optimization/guide/install.
How can I contribute to the project?
Review the contribution guidelines in the repository. Requests and bugs are tracked through GitHub issues.
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