ckswjd99

ckswjd99's Stars

• Zhen-Dong/Awesome-Quantization-Papers

  List of papers related to neural network quantization in recent AI conferences and journals.

  48739

• htqin/BiBench

  [ICML 2023] This project is the official implementation of our accepted ICML 2023 paper BiBench: Benchmarking and Analyzing Network Binarization.

  Language:Python544

• eghouti/BinaryConnect

  Implementation of BinaryConnect on Pytorch

  Language:Jupyter Notebook368

• google/XNNPACK

  High-efficiency floating-point neural network inference operators for mobile, server, and Web

  Language:C1.9k376

• huawei-noah/AdderNet

  Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"

  Language:Python955187

• Efficient-ML/Awesome-Model-Quantization

  A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo.

  1.9k209

• ridgerchu/matmulfreellm

  Implementation for MatMul-free LM.

  Language:Python2.9k187

• bobby-he/Neural_Tangent_Kernel

  Language:Jupyter Notebook678

• matthias-wright/cifar10-resnet

  PyTorch implementation of a 9-layer ResNet for CIFAR-10.

  Language:Python115

• kuangliu/pytorch-cifar

  95.47% on CIFAR10 with PyTorch

  Language:Python6.1k2.1k

• IBM/pytorch-seq2seq

  An open source framework for seq2seq models in PyTorch.

  Language:Python1.5k375

• akamaster/pytorch_resnet_cifar10

  Proper implementation of ResNet-s for CIFAR10/100 in pytorch that matches description of the original paper.

  Language:Python1.2k334

• omihub777/MLP-Mixer-CIFAR

  PyTorch implementation of Mixer-nano (#parameters is 0.67M, originally Mixer-S/16 has 18M) with 90.83 % acc. on CIFAR-10. Training from scratch.

  Language:Python296

• liux2/RNN-on-wikitext2

  Pytorch of RNN and LSTM on wikitext2 dataset

  Language:Jupyter Notebook73

• orobix/fwdgrad

  Implementation of "Gradients without backpropagation" paper (https://arxiv.org/abs/2202.08587) using functorch

  Language:Python1009

• DefTruth/Awesome-LLM-Inference

  📖A curated list of Awesome LLM/VLM Inference Papers with codes, such as FlashAttention, PagedAttention, Parallelism, etc. 🎉🎉

  3.1k207

• kentaroy47/vision-transformers-cifar10

  Let's train vision transformers (ViT) for cifar 10!

  Language:Python563112

• graykode/gpt-2-Pytorch

  Simple Text-Generator with OpenAI gpt-2 Pytorch Implementation

  Language:Python977227

• OPTML-Group/DeepZero

  [ICLR'24] "DeepZero: Scaling up Zeroth-Order Optimization for Deep Model Training" by Aochuan Chen*, Yimeng Zhang*, Jinghan Jia, James Diffenderfer, Jiancheng Liu, Konstantinos Parasyris, Yihua Zhang, Zheng Zhang, Bhavya Kailkhura, Sijia Liu

  Language:Python476

• L0SG/feedback-alignment-pytorch

  Implementation of feedback alignment learning in PyTorch

  Language:Python296

• princeton-nlp/MeZO

  [NeurIPS 2023] MeZO: Fine-Tuning Language Models with Just Forward Passes. https://arxiv.org/abs/2305.17333

  Language:Python1.1k66

• weiaicunzai/pytorch-cifar100

  Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet, WideResNet)

  Language:Python4.4k1.2k

• thunlp/Knowledge-Inheritance

  Source code for paper: Knowledge Inheritance for Pre-trained Language Models

  Language:Python384

• VITA-Group/LiGO

  [ICLR 2023] "Learning to Grow Pretrained Models for Efficient Transformer Training" by Peihao Wang, Rameswar Panda, Lucas Torroba Hennigen, Philip Greengard, Leonid Karlinsky, Rogerio Feris, David Cox, Zhangyang Wang, Yoon Kim

  Language:Python849

• google-research/growneuron

  Language:Jupyter Notebook539

• Prev/clustered-imagenet-labels

  A dataset for production-friendly image classifiers

  Language:Python3

• lucidrains/vit-pytorch

  Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

  Language:Python21.2k3.1k

• chengyangfu/pytorch-vgg-cifar10

  This is the PyTorch implementation of VGG network trained on CIFAR10 dataset

  Language:Jupyter Notebook347116

• NVIDIA/nccl

  Optimized primitives for collective multi-GPU communication

  Language:C++3.3k840

• cakeng/ASPEN

  This is the proof-of-concept CPU implementation of ASPEN used for the NeurIPS'23 paper ASPEN: Breaking Operator Barriers for Efficient Parallelization of Deep Neural Networks.

  Language:Assembly111