synxlin / nn-compression
A Pytorch implementation of Neural Network Compression (pruning, deep compression, channel pruning)
☆153Updated 5 months ago
Alternatives and similar repositories for nn-compression:
Users that are interested in nn-compression are comparing it to the libraries listed below
- ☆213Updated 6 years ago
- Pytorch version for weight pruning for Murata Group's CREST project☆57Updated 6 years ago
- PyTorch Implementation of Weights Pruning☆184Updated 6 years ago
- A PyTorch implementation of "Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights"☆164Updated 4 years ago
- This repo contains the official Pytorch reimplementation of the paper "NetAdapt: Platform-Aware Neural Network Adaptation for Mobile Appl…☆182Updated last year
- Code for the NuerIPS'19 paper "Gate Decorator: Global Filter Pruning Method for Accelerating Deep Convolutional Neural Networks"☆196Updated 4 years ago
- LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks☆240Updated 2 years ago
- [CVPR 2020] APQ: Joint Search for Network Architecture, Pruning and Quantization Policy☆156Updated 4 years ago
- Learning both Weights and Connections for Efficient Neural Networks https://arxiv.org/abs/1506.02626☆175Updated 2 years ago
- CNN channel pruning, LeGR, MorphNet, AMC. Codebase for paper "LeGR: Filter Pruning via Learned Global Ranking"☆114Updated 4 years ago
- [ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices☆166Updated 3 years ago
- [CVPR'20] ZeroQ: A Novel Zero Shot Quantization Framework☆274Updated last year
- (ECCV'2020 Oral)EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning☆306Updated 2 years ago
- Pruning Neural Networks with Taylor criterion in Pytorch☆315Updated 5 years ago
- Soft Filter Pruning for Accelerating Deep Convolutional Neural Networks☆377Updated 5 years ago
- [ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices☆433Updated last year
- papers about model compression☆166Updated last year
- Mayo: Auto-generation of hardware-friendly deep neural networks. Dynamic Channel Pruning: Feature Boosting and Suppression.☆114Updated 5 years ago
- PyTorch implementation of Data Free Quantization Through Weight Equalization and Bias Correction.☆259Updated last year
- Quantization of Convolutional Neural networks.☆239Updated 4 months ago
- Implements quantized distillation. Code for our paper "Model compression via distillation and quantization"☆331Updated 4 months ago
- PyTorch implementation of 'Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding' by …☆417Updated 4 years ago
- Class Project for 18663 - Implementation of FBNet (Hardware-Aware DNAS)☆33Updated 5 years ago
- Prune DNN using Alternating Direction Method of Multipliers (ADMM)☆107Updated 4 years ago
- On-the-fly Structured Pruning for PyTorch models. This library implements several attributions metrics and structured pruning utils for n…☆162Updated 4 years ago
- [CVPR 2019, Oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision☆375Updated 3 years ago
- Repository to track the progress in model compression and acceleration☆105Updated 3 years ago
- MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning. In ICCV 2019.☆352Updated 4 years ago
- alibabacloud-quantization-networks☆121Updated 5 years ago