IntelLabs / distillerLinks
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://intellabs.github.io/distiller
☆4,402Updated 2 years ago
Alternatives and similar repositories for distiller
Users that are interested in distiller are comparing it to the libraries listed below
Sorting:
- Rethinking the Value of Network Pruning (Pytorch) (ICLR 2019)☆1,516Updated 5 years ago
- [ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment☆1,936Updated last year
- Model analyzer in PyTorch☆1,498Updated 2 years ago
- Awesome Knowledge Distillation☆3,759Updated last week
- A curated list of neural network pruning resources.☆2,479Updated last year
- Differentiable architecture search for convolutional and recurrent networks☆3,979Updated 4 years ago
- [ICLR 2019] ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware☆1,451Updated last year
- An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.☆2,911Updated 2 years ago
- Pretrained EfficientNet, EfficientNet-Lite, MixNet, MobileNetV3 / V2, MNASNet A1 and B1, FBNet, Single-Path NAS☆1,581Updated last year
- Flops counter for neural networks in pytorch framework☆2,951Updated 2 months ago
- PyTorch implementation of "Efficient Neural Architecture Search via Parameters Sharing"☆2,724Updated 2 years ago
- The convertor/conversion of deep learning models for different deep learning frameworks/softwares.☆3,251Updated 2 years ago
- MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Co…☆5,815Updated 2 months ago
- Codebase for Image Classification Research, written in PyTorch.☆2,165Updated last year
- On the Variance of the Adaptive Learning Rate and Beyond☆2,550Updated 4 years ago
- Collection of recent methods on (deep) neural network compression and acceleration.☆951Updated 6 months ago
- micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantiz…☆2,262Updated 5 months ago
- Count the MACs / FLOPs of your PyTorch model.☆5,049Updated last year
- A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility☆1,969Updated 2 years ago
- Quantized Neural Network PACKage - mobile-optimized implementation of quantized neural network operators☆1,547Updated 6 years ago
- PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference☆885Updated 6 years ago
- ☆669Updated 4 years ago
- A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch☆8,832Updated this week
- Memory consumption and FLOP count estimates for convnets☆930Updated 6 years ago
- Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis)☆2,319Updated 3 years ago
- Improving Convolutional Networks via Attention Transfer (ICLR 2017)☆1,461Updated 7 years ago
- An optimizer that trains as fast as Adam and as good as SGD.☆2,909Updated 2 years ago
- ☆1,504Updated 5 years ago
- Model summary in PyTorch similar to `model.summary()` in Keras☆4,062Updated last year
- Unofficial implementation of the ImageNet, CIFAR 10 and SVHN Augmentation Policies learned by AutoAugment using pillow☆1,488Updated 2 years ago