111 Open source projects that are alternatives of or similar to Awesome Pruning

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

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

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

Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks

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

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

[ICLR'21] PyTorch code for our paper "Neural Pruning via Growing Regularization"

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

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

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

Infrastructures™ for Machine Learning Training/Inference in Production.

[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

A pytorch pruning toolkit for structured neural network pruning and layer dependency maintaining.

(CVPR 2021, Oral) Dynamic Slimmable Network

Efficient-Computing

Data Efficient Model Compression

Pruning and quantization for SSD. Model compression.

🔌⚡ Nuxt module to prune html before sending it to the browser (it removes elements matching CSS selector(s)), useful for boosting performance showing a different HTML for bots/audits by removing all the scripts with dynamic rendering

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.

Pruning and other network surgery for trained Keras models.

Unofficial Pytorch implementation of Deep Compression in CIFAR10

OpenMMLab Model Compression Toolbox and Benchmark.

yolov3 network slimming剪枝的一种实现

This repository contains code to replicate the experiments given in NeurIPS 2019 paper "One ticket to win them all: generalizing lottery ticket initializations across datasets and optimizers"

Remove/Backup – settings & cli for macOS (OS X) – DataGrip, AppCode, CLion, Gogland, IntelliJ, PhpStorm, PyCharm, Rider, RubyMine, WebStorm

Keras model convolutional filter pruning package

Lightweight and Scalable framework that combines mainstream algorithms of Click-Through-Rate prediction based computational DAG, philosophy of Parameter Server and Ring-AllReduce collective communication.

Papers for deep neural network compression and acceleration

PyTorch implementation of "Pruning Filters For Efficient ConvNets"

Deep Learning for Computer Vision (CommE 5052) in NTU

knowledge distillation papers

Yolov5 distillation training | Yolov5知识蒸馏训练，支持训练自己的数据

PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference

🤖 A machine learning framework for audio, text, image, video, or .CSV files (50+ featurizers and 15+ model trainers).

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

Attempting feature map prunning on a CNN trained for Japanese OCR

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

Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolution Layers https://arxiv.org/abs/1802.00124

Your local Flux surgeon

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

🛠️ Tools for Transformers compression using PyTorch Lightning ⚡

Learnable Embedding Space for Efficient Neural Architecture Compression

YOLO ModelCompression MultidatasetTraining

pytorch realtime multi person keypoint estimation

pytorch implementation of Structured Bayesian Pruning

Embedded and mobile deep learning research resources

One Person, One Model, One World: Learning Continual User Representation without Forgetting

Group Fisher Pruning for Practical Network Compression(ICML2021)

FasterAI: A repository for making smaller and faster models with the FastAI library.

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.

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

Pytorch implementation of various Knowledge Distillation (KD) methods.

A PyTorch-based model pruning toolkit for pre-trained language models

A package to make do Network Slimming a little easier

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

Implement of Dynamic Model Pruning with Feedback with pytorch

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

Neural network model repository for highly sparse and sparse-quantized models with matching sparsification recipes

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

A research library for pytorch-based neural network pruning, compression, and more.