model-compression
There are 310 repositories under model-compression topic.
microsoft/nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
huawei-noah/Efficient-AI-Backbones
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
dkozlov/awesome-knowledge-distillation
Awesome Knowledge Distillation
huawei-noah/Pretrained-Language-Model
Pretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.
VainF/Torch-Pruning
[CVPR 2023] DepGraph: Towards Any Structural Pruning; LLMs, Vision Foundation Models, etc.
Tencent/PocketFlow
An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.
FLHonker/Awesome-Knowledge-Distillation
Awesome Knowledge-Distillation. 分类整理的知识蒸馏paper(2014-2021)。
he-y/Awesome-Pruning
A curated list of neural network pruning resources.
666DZY666/micronet
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
Efficient-ML/Awesome-Model-Quantization
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.
haitongli/knowledge-distillation-pytorch
A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility
AberHu/Knowledge-Distillation-Zoo
Pytorch implementation of various Knowledge Distillation (KD) methods.
tensorflow/model-optimization
A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.
microsoft/NeuronBlocks
NLP DNN Toolkit - Building Your NLP DNN Models Like Playing Lego
huawei-noah/Efficient-Computing
Efficient computing methods developed by Huawei Noah's Ark Lab
ethanhe42/channel-pruning
Channel Pruning for Accelerating Very Deep Neural Networks (ICCV'17)
MingSun-Tse/Efficient-Deep-Learning
Collection of recent methods on (deep) neural network compression and acceleration.
horseee/DeepCache
[CVPR 2024] DeepCache: Accelerating Diffusion Models for Free
guan-yuan/Awesome-AutoML-and-Lightweight-Models
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.
alibaba/TinyNeuralNetwork
TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework.
lhyfst/knowledge-distillation-papers
knowledge distillation papers
Zhen-Dong/Awesome-Quantization-Papers
List of papers related to neural network quantization in recent AI conferences and journals.
SqueezeAILab/SqueezeLLM
[ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization
cnkuangshi/LightCTR
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.
SforAiDl/KD_Lib
A Pytorch Knowledge Distillation library for benchmarking and extending works in the domains of Knowledge Distillation, Pruning, and Quantization.
he-y/filter-pruning-geometric-median
Filter Pruning via Geometric Median for Deep Convolutional Neural Networks Acceleration (CVPR 2019 Oral)
cedrickchee/awesome-ml-model-compression
Awesome machine learning model compression research papers, quantization, tools, and learning material.
iamhankai/ghostnet.pytorch
[CVPR2020] GhostNet: More Features from Cheap Operations
microsoft/archai
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
Zhen-Dong/HAWQ
Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.
mit-han-lab/amc
[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices
1duo/awesome-ai-infrastructures
Infrastructures™ for Machine Learning Training/Inference in Production.
chester256/Model-Compression-Papers
Papers for deep neural network compression and acceleration
pratyushasharma/laser
The Truth Is In There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
he-y/soft-filter-pruning
Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks
SqueezeAILab/KVQuant
[NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization