AldrichZeng / Graduation-Design
基于剪枝的神经网络压缩与加速
☆21Updated 5 years ago
Alternatives and similar repositories for Graduation-Design:
Users that are interested in Graduation-Design are comparing it to the libraries listed below
- 模型压缩demo(剪枝、量化、知识蒸馏)☆71Updated 4 years ago
- ☆36Updated 6 years ago
- B站Efficient-Neural-Network学习分享的配套代码☆295Updated 3 years ago
- 基于提前退出部分样本原理而实现的带分支网络(supported by chainer)☆45Updated 5 years ago
- ☆17Updated 6 years ago
- Compression of Deep Neural Networks LeNet-300-100 and LeNet-5 trained on MNIST and CIFAR-10 using Quantization, Knowledge Distillation & …☆19Updated 5 years ago
- Pruned model: VGG & ResNet-50☆17Updated 5 years ago
- Unofficial Pytorch implementation of Deep Compression in CIFAR10☆35Updated 3 years ago
- Base to channel pruned to ResNet18 model☆145Updated 2 years ago
- 对yolov4进行通道剪枝☆15Updated 2 years ago
- Quantize,Pytorch,Vgg16,MobileNet☆42Updated 4 years ago
- Pytorch Implementationg of “Learning Efficient Convolutional Networks through Network Slimming”☆77Updated 6 years ago
- An implementation of ResNet with mixup and cutout regularizations and soft filter pruning.☆16Updated 4 years ago
- Pruning Filters For Efficient ConvNets, PyTorch Implementation.☆30Updated 5 years ago
- Training models with ternary quantized weights using PyTorch☆11Updated 5 years ago
- 卷积神经网络CNN在cifar10上的应用☆28Updated 6 years ago
- OpenPose uses Pytorch for static quantization, saving, and loading of models☆86Updated 3 years ago
- An 8bit automated quantization conversion tool for the pytorch (Post-training quantization based on KL divergence)☆33Updated 5 years ago
- Learning both Weights and Connections for Efficient Neural Networks https://arxiv.org/abs/1506.02626☆18Updated 4 years ago
- Quantize pytorch model, support post-training quantization and quantization aware training methods☆13Updated last year
- 用于 MobileNetV3 在自定义数据集上的量化,模型压缩90%而精度几乎不受影响,论文:HAQ: Hardware-Aware Automated Quantization with Mixed Precision☆17Updated 3 years ago
- yolov3_tiny implement on tensoeflow for int8 quantization (tflite)☆29Updated 6 years ago
- Model Compression 1. Pruning(BN Pruning) 2. Knowledge Distillation (Hinton) 3. Quantization (MNN) 4. Deployment (MNN)☆79Updated 4 years ago
- In this repository using the sparse training, group channel pruning and knowledge distilling for YOLOV4,☆31Updated last year
- A reproduction of PRUNING FILTERS FOR EFFICIENT CONVNETS☆28Updated 4 years ago
- A pytorch implementation of dorefa quantization☆113Updated 5 years ago
- Personal Pytorch toy script.☆67Updated 3 years ago
- ☆11Updated 5 years ago
- Pruning and quantization for SSD. Model compression.☆30Updated 4 years ago
- Implementation of ENAS for CNNs on CIFAR 10☆11Updated 5 years ago