A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
-
Updated
Nov 4, 2024 - Python
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering.
A nnie quantization aware training tool on pytorch.
Code for "Quantized Densely Connected U-Nets for Efficient Landmark Localization" (ECCV 2018) and "CU-Net: Coupled U-Nets" (BMVC 2018 oral)
Add a description, image, and links to the quantized-training topic page so that developers can more easily learn about it.
To associate your repository with the quantized-training topic, visit your repo's landing page and select "manage topics."