146 Open source projects that are alternatives of or similar to Hawq

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

Infrastructures™ for Machine Learning Training/Inference in Production.

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

An Open Source Deep Learning Inference Engine Based on FPGA

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 Pytorch Knowledge Distillation library for benchmarking and extending works in the domains of Knowledge Distillation, Pruning, and Quantization.

针对pytorch模型的自动化模型结构分析和修改工具集，包含自动分析模型结构的模型压缩算法库

Awesome machine learning model compression research papers, tools, and learning material.

CVPR 2021 : Zero-shot Adversarial Quantization (ZAQ)

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

BitPack is a practical tool to efficiently save ultra-low precision/mixed-precision quantized models.

[NeurIPS'2019] Shupeng Gui, Haotao Wang, Haichuan Yang, Chen Yu, Zhangyang Wang, Ji Liu, “Model Compression with Adversarial Robustness: A Unified Optimization Framework”

Embedded and mobile deep learning research resources

Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。

A high performance, distributed RPC framework.（分布式服务框架XXL-RPC）

[CVPR2020] GhostNet: More Features from Cheap Operations

Powerful, automated analysis and design of quantum microwave chips & devices [Energy-Participation Ratio and more]

Compressing Representations for Self-Supervised Learning

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

Data Efficient Model Compression

Robotics Toolbox for Python

Brevitas: quantization-aware training in PyTorch

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

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Dice.com repo to accompany the dice.com 'Vectors in Search' talk by Simon Hughes, from the Activate 2018 search conference, and the 'Searching with Vectors' talk from Haystack 2019 (US). Builds upon my conceptual search and semantic search work from 2015

Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)

SOFARPC is a high-performance, high-extensibility, production-level Java RPC framework.

A treasure chest for image classification powered by PaddlePaddle

Training & Quantization of embedded friendly Deep Learning / Machine Learning / Computer Vision models

Pytorch implementation of various Knowledge Distillation (KD) methods.

FrostNet: Towards Quantization-Aware Network Architecture Search

AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

A curated list of neural network pruning resources.

knowledge distillation papers

Jupiter是一款性能非常不错的, 轻量级的分布式服务框架

Lossy PNG compressor — pngquant command based on libimagequant library

Simulate quantization and quantization aware training for MXNet-Gluon models.

Palette quantization library that powers pngquant and other PNG optimizers

A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility

Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration (CVPR 2019 Oral)

An internal improved version of Hessian powered by Ant Financial.

SDK for TEE AI Stick (includes model training script, inference library, examples)

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

[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices

Papers for deep neural network compression and acceleration

The Easiest Knowledge Distillation Library for Lightweight Deep Learning

Trainable models and NN optimization tools

Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

Dataflow compiler for QNN inference on FPGAs

This project is the official implementation of our accepted ICLR 2021 paper BiPointNet: Binary Neural Network for Point Clouds.

a golang micro-service framework compatible with alibaba dubbo

QKeras: a quantization deep learning library for Tensorflow Keras

NLP DNN Toolkit - Building Your NLP DNN Models Like Playing Lego

pytorch implementation of "Differentiable Soft Quantization: Bridging Full-Precision and Low-Bit Neural Networks"

libimagequant (pngquant) bindings for the Rust language

Easy-to-use UI for automatically sparsifying neural networks and creating sparsification recipes for better inference performance and a smaller footprint

[NeurIPS'21] "Chasing Sparsity in Vision Transformers: An End-to-End Exploration" by Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang

🎨 Simple color palette quantization using MMCQ

Model Compression Based on Geoffery Hinton's Logit Regression Method in Keras applied to MNIST 16x compression over 0.95 percent accuracy.An Implementation of "Distilling the Knowledge in a Neural Network - Geoffery Hinton et. al"