Deep-Compression-AlexNet

Model compression

This project demonstrates a method to compress the size of a neural network model without sacrificing accuracy.

Deep Compression on AlexNet

GitHub
657 stars
51 watching
208 forks
Language: Python
last commit: over 2 years ago
Linked from 1 awesome list


Backlinks from these awesome lists:

Related projects:

Repository Description Stars
jalexvig/associative_compression_networks An implementation of associative compression networks using machine learning techniques in Python 43
forresti/squeezenet Provides pre-trained models and training configurations for a deep neural network architecture optimized for image classification tasks 2,176
brightmart/xlnet_zh Trains a large Chinese language model on massive data and provides a pre-trained model for downstream tasks 230
hassony2/inflated_convnets_pytorch Creates inflated versions of 2D neural networks with transferred ImageNet weights for use in 3D applications 148
ymcui/chinese-xlnet Provides pre-trained models for Chinese natural language processing tasks using the XLNet architecture 1,653
preritj/segmentation Deep learning models for semantic segmentation of images 100
microsoft/archai Automates the search for optimal neural network configurations in deep learning applications 467
alexbrillant/multi-layer-perceptron An implementation of a multi-layer neural network in Python, allowing users to train and use the network for classification tasks. 5
hszhao/pspnet A PyTorch implementation of a deep learning model for semantic image segmentation 1,593
abbypa/nnproject_deepmask A deep learning implementation of an object segmentation algorithm. 187
isht7/pytorch-deeplab-resnet A deep learning model implementation of the DeepLab ResNet architecture for image segmentation tasks. 602
naturalintelligence/nimnjs Highly compressed JavaScript object/JSON implementation 45
ahmedfgad/numpyann An implementation of artificial neural networks using NumPy for building regression and classification models. 98
intel/neural-compressor Tools and techniques for optimizing large language models on various frameworks and hardware platforms. 2,229
canqin001/pointdan Develops a deep learning model for domain adaptation on 3D point cloud data 130