SforAiDl / KD_LibLinks
A Pytorch Knowledge Distillation library for benchmarking and extending works in the domains of Knowledge Distillation, Pruning, and Quantization.
ā640Updated 2 years ago
Alternatives and similar repositories for KD_Lib
Users that are interested in KD_Lib are comparing it to the libraries listed below
Sorting:
- A coding-free framework built on PyTorch for reproducible deep learning studies. PyTorch Ecosystem. š26 knowledge distillation methods pā¦ā1,533Updated last week
- Knowledge Distillation: CVPR2020 Oral, Revisiting Knowledge Distillation via Label Smoothing Regularizationā584Updated 2 years ago
- PyTorch library to facilitate development and standardized evaluation of neural network pruning methods.ā430Updated 2 years ago
- Pytorch implementation of various Knowledge Distillation (KD) methods.ā1,710Updated 3 years ago
- A large scale study of Knowledge Distillation.ā220Updated 5 years ago
- Escaping the Big Data Paradigm with Compact Transformers, 2021 (Train your Vision Transformers in 30 mins on CIFAR-10 with a single GPU!)ā536Updated 9 months ago
- A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibilityā1,957Updated 2 years ago
- Awesome machine learning model compression research papers, quantization, tools, and learning material.ā527Updated 10 months ago
- knowledge distillation papersā758Updated 2 years ago
- AugMix: A Simple Data Processing Method to Improve Robustness and Uncertaintyā990Updated 2 months ago
- š Toolbox to extend PyTorch functionalitiesā421Updated last year
- Estimate/count FLOPS for a given neural network using pytorchā305Updated 3 years ago
- NFNets and Adaptive Gradient Clipping for SGD implemented in PyTorch. Find explanation at tourdeml.github.io/blog/ā347Updated last year
- Open-source code for paper "Dataset Distillation"ā811Updated last month
- On-the-fly Structured Pruning for PyTorch models. This library implements several attributions metrics and structured pruning utils for nā¦ā167Updated 5 years ago
- Collection of recent methods on (deep) neural network compression and acceleration.ā948Updated 4 months ago
- Code for Noisy Student Training. https://arxiv.org/abs/1911.04252ā764Updated 4 years ago
- Is the attention layer even necessary? (https://arxiv.org/abs/2105.02723)ā486Updated 4 years ago
- Unofficial PyTorch Reimplementation of RandAugment.ā636Updated 2 years ago
- Compare neural networks by their feature similarityā369Updated 2 years ago
- Summary, Code for Deep Neural Network Quantizationā552Updated last month
- A general and accurate MACs / FLOPs profiler for PyTorch modelsā624Updated last week
- Official PyTorch implementation of "A Comprehensive Overhaul of Feature Distillation" (ICCV 2019)ā417Updated 5 years ago
- ā605Updated last month
- [ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deploymentā1,927Updated last year
- Learning Rate Warmup in PyTorchā410Updated last month
- A curated list of neural network pruning resources.ā2,468Updated last year
- MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tricks. In NeurIPS 2020 workshop.ā697Updated 3 years ago
- Gradually-Warmup Learning Rate Scheduler for PyTorchā991Updated 9 months ago
- mixup: Beyond Empirical Risk Minimizationā1,185Updated 3 years ago