upcJack

upcJack's Stars

• Chernobyllight/SaMST

  Pluggable Style Representation Learning for Multi-Style Transfer

  Language:Python12

• CuiYing123456/GQFedWAvg

  paper: GQFedWAvg: Optimization-Based Quantized Federated Learning in General Edge Computing Systems, to appear in IEEE TWC

  Language:MATLAB8

• Rainysponge/SLPerf

  Language:Python101

• seotaijiya/LLM_OPT

  Source code for LLM based optimization for wireless communication

  Language:Python7

• kentaroy47/vision-transformers-cifar10

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

  Language:Python561111

• huggingface/pytorch-image-models

  The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

  Language:Python32.7k4.8k

• faresmalik/FeSViBS

  Source code for MICCAI 2023 paper entitled: 'FeSViBS: Federated Split Learning of Vision Transformer with Block Sampling'

  Language:Python202

• wangsr126/MAE-Lite

  Official implement for ICML2023 paper: "A Closer Look at Self-Supervised Lightweight Vision Transformers"

  Language:Python1199

• FDU-INC/Split_LoRA

  Language:Python155

• s-chh/PyTorch-Scratch-Vision-Transformer-ViT

  Simple and easy to understand PyTorch implementation of Vision Transformer (ViT) from scratch, with detailed steps. Tested on common datasets like MNIST, CIFAR10, and more.

  Language:Python12618

• Cydia2018/ViT-cifar10-pruning

  Vision Transformer Pruning

  Language:Python5411

• lancopku/Embedding-Poisoning

  Code for the paper "Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models" (NAACL-HLT 2021)

  Language:Python397

• karpathy/nanoGPT

  The simplest, fastest repository for training/finetuning medium-sized GPTs.

  Language:Python38.1k6.1k

• ymcui/Chinese-LLaMA-Alpaca-3

  中文羊驼大模型三期项目 (Chinese Llama-3 LLMs) developed from Meta Llama 3

  Language:Python1.8k154

• huggingface/peft

  🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.

  Language:Python16.8k1.7k

• hiyouga/LLaMA-Factory

  Unified Efficient Fine-Tuning of 100+ LLMs (ACL 2024)

  Language:Python36.8k4.5k

• google-research/bert

  TensorFlow code and pre-trained models for BERT

  Language:Python38.4k9.6k

• neelsjain/NEFTune

  Official repository of NEFTune: Noisy Embeddings Improves Instruction Finetuning

  Language:Python38820

• jiangfeibo/LAMSC

  The source code of 《Large AI Model-Based Semantic Communications》

  Language:Python287

• chunbaobao/Deep-JSCC-PyTorch

  A implement of Deep JSCC for wireless image transmission by PyTorch

  Language:Jupyter Notebook7411

• zhanwen/MathModel

  研究生数学建模，本科生数学建模、数学建模竞赛优秀论文，数学建模算法，LaTeX论文模板，算法思维导图，参考书籍，Matlab软件教程，PPT

  Language:TeX8.4k2.1k

• poojahira/gtsrb-pytorch

  PyTorch implementation of Kaggle GTSRB challenge with 99.8% accuracy

  Language:Python5413

• zoubohao/DenoisingDiffusionProbabilityModel-ddpm-

  This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.

  Language:Python1.7k180

• openai/CLIP

  CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

  Language:Jupyter Notebook26.7k3.4k

• yasamanhbn/Diffusion-Model-Cifar10

  Implementation of Diffusion Model for Cifar10

  Language:Jupyter Notebook10

• MMorafah/FedZoo-Bench

  FedZoo-Bench: An open source PyTorch libarary for federated learning with implementation of more than 22 algorithms

  Language:Python153

• OpenRL-Lab/Wandb_Tutorial

  How to use wandb?

  Language:Python60149

• seyoungahn/FedDif

  Official implementations for "Communication-Efficient Diffusion Strategy for Performance Improvement of Federated Learning with Non-IID Data" paper.

  Language:Python203

• abarankab/DDPM

  PyTorch DDPM implementation

  Language:Python697109

• owenliang/mnist-dits

  Diffusion Transformers (DiTs) trained on MNIST dataset

  Language:Python7711