quantization

Lossy PNG compressor — pngquant command based on libimagequant library

Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller

A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks

Pretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.

Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.

Trainable models and NN optimization tools

PaddleSlim is an open-source library for deep model compression and architecture search.

Neural network inference engine that delivers GPU-class performance for sparsified models on CPUs

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 list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo.

Brevitas: quantization-aware training in PyTorch

🏎️ Accelerate training and inference of 🤗 Transformers with easy to use hardware optimization tools

Embedded and mobile deep learning research resources

Palette quantization library that powers pngquant and other PNG optimizers

Neural Network Compression Framework for enhanced OpenVINO™ inference

An Open-Source Package for Deep Learning to Hash (DeepHash)

Intel® Neural Compressor (formerly known as Intel® Low Precision Optimization Tool), targeting to provide unified APIs for network compression technologies, such as low precision quantization, sparsity, pruning, knowledge distillation, across different deep learning frameworks to pursue optimal inference performance.

QKeras: a quantization deep learning library for Tensorflow Keras

PyTorch Project Specification.

Must-read papers on deep learning to hash (DeepHash)

Fast inference engine for Transformer models

⚡ boost inference speed of T5 models by 5x & reduce the model size by 3x.

[CVPR 2019, Oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision

Infrastructures™ for Machine Learning Training/Inference in Production.

PPL Quantization Tool (PPQ) is a powerful offline neural network quantization tool.