mit-han-lab / once-for-allLinks
[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment
☆1,925Updated last year
Alternatives and similar repositories for once-for-all
Users that are interested in once-for-all are comparing it to the libraries listed below
Sorting:
- Mobile vision models and code☆911Updated 4 months ago
- Rethinking the Value of Network Pruning (Pytorch) (ICLR 2019)☆1,513Updated 5 years ago
- [ICLR 2019] ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware☆1,442Updated 10 months ago
- Collection of recent methods on (deep) neural network compression and acceleration.☆948Updated 3 months ago
- A curated list of neural network pruning resources.☆2,462Updated last year
- Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distille…☆4,398Updated 2 years ago
- Automated deep learning algorithms implemented in PyTorch.☆1,582Updated 3 years ago
- Flops counter for neural networks in pytorch framework☆2,909Updated 5 months ago
- Codebase for Image Classification Research, written in PyTorch.☆2,156Updated last year
- [ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices☆443Updated last year
- Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)☆2,295Updated 2 years ago
- PyTorch library to facilitate development and standardized evaluation of neural network pruning methods.☆430Updated 2 years ago
- Pretrained EfficientNet, EfficientNet-Lite, MixNet, MobileNetV3 / V2, MNASNet A1 and B1, FBNet, Single-Path NAS☆1,572Updated last year
- ☆668Updated 3 years ago
- Slimmable Networks, AutoSlim, and Beyond, ICLR 2019, and ICCV 2019☆922Updated 2 years ago
- Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"☆961Updated 3 years ago
- A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility☆1,952Updated 2 years ago
- A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. 🏆26 knowledge distillation methods p…☆1,526Updated last week
- Summary, Code for Deep Neural Network Quantization☆549Updated 3 weeks ago
- Collection of common code that's shared among different research projects in FAIR computer vision team.☆2,148Updated last week
- micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantiz…☆2,253Updated 2 months ago
- Model analyzer in PyTorch☆1,486Updated 2 years ago
- Papers for deep neural network compression and acceleration☆399Updated 4 years ago
- A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures,…☆852Updated 4 years ago
- Pytorch implementation of various Knowledge Distillation (KD) methods.☆1,706Updated 3 years ago
- A general and accurate MACs / FLOPs profiler for PyTorch models☆619Updated last year
- Code for: "And the bit goes down: Revisiting the quantization of neural networks"☆633Updated 4 years ago
- Awesome machine learning model compression research papers, quantization, tools, and learning material.☆526Updated 9 months ago
- AutoML tools chain☆851Updated 2 years ago
- AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.☆2,364Updated this week