DURGESH716/model-optimization
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
TensorFlow Model Optimization Toolkit
The TensorFlow Model Optimization Toolkit is a suite of tools that users,
both novice and advanced, can use to optimize machine learning models for
deployment and execution.
Supported techniques include quantization and pruning for sparse weights.
There are APIs built specifically for Keras.
For an overview of this project and individual tools, the optimization gains,
and our roadmap refer to
tensorflow.org/model_optimization.
The website also provides various tutorials and API docs.
The toolkit provides stable Python APIs.
Installation
For installation instructions, see
tensorflow.org/model_optimization/guide/install.
Contribution guidelines
If you want to contribute to TensorFlow Model Optimization, be sure to review
the contribution guidelines. This project adheres to
TensorFlow's
code of conduct.
By participating, you are expected to uphold this code.
We use
GitHub issues for
tracking requests and bugs.
Maintainers
| Subpackage | Maintainers |
|---|---|
| tfmot.clustering | Arm ML Tooling |
| tfmot.quantization | TensorFlow Model Optimization |
| tfmot.sparsity | TensorFlow Model Optimization |
Community
As part of TensorFlow, we're committed to fostering an open and welcoming
environment.
- TensorFlow Blog: Stay up to date on content
from the TensorFlow team and best articles from the community.