tensorflow/model-optimization
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
This toolkit helps machine learning engineers and researchers make their trained Keras and TensorFlow models smaller and faster. It takes an existing, functional machine learning model and applies optimization techniques like quantization or pruning. The output is a more efficient model that performs similarly but requires less computational power and memory, ideal for deploying on devices with limited resources.
1,565 stars. Actively maintained with 1 commit in the last 30 days.
Use this if you need to deploy a Keras or TensorFlow machine learning model to environments with tight constraints on processing power, memory, or battery life, such as mobile phones or embedded systems.
Not ideal if your primary goal is to improve model accuracy or if you are not working with Keras or TensorFlow models.
Stars
1,565
Forks
346
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 08, 2026
Commits (30d)
1
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