sunnyxuejj

sunnyxuejj's Stars

• bytedance/ABQ-LLM

  An acceleration library that supports arbitrary bit-width combinatorial quantization operations

  Language:C++22323

• yuhuixu1993/qa-lora

  Official PyTorch implementation of QA-LoRA

  Language:Python11510

• haotian-liu/LLaVA

  [NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.

  Language:Python20.1k2.2k

• BradyFU/Awesome-Multimodal-Large-Language-Models

  :sparkles::sparkles:Latest Advances on Multimodal Large Language Models

  12.5k802

• liguodongiot/llm-action

  本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）

  Language:HTML10.4k1k

• hahnyuan/RPTQ4LLM

  Reorder-based post-training quantization for large language model

  Language:Python18111

• HuangOwen/Awesome-LLM-Compression

  Awesome LLM compression research papers and tools.

  1.2k74

• IST-DASLab/sparsegpt

  Code for the ICML 2023 paper "SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot".

  Language:Python71095

• SMILELab-FL/FedPETuning

  Language:Python5817

• huggingface/peft

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

  Language:Python16.3k1.6k

• alibaba/FederatedScope

  An easy-to-use federated learning platform

  Language:Python1.3k210

• 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:Python32.2k4.8k

• Hhhhhhao/Noisy-Model-Learning

  Language:Python303

• LAION-AI/CLIP_benchmark

  CLIP-like model evaluation

  Language:Jupyter Notebook61078

• qingsongedu/Awesome-TimeSeries-SpatioTemporal-LM-LLM

  A professional list on Large (Language) Models and Foundation Models (LLM, LM, FM) for Time Series, Spatiotemporal, and Event Data.

  91967

• FLAIR-THU/VFLAIR

  THU-AIR Vertical Federated Learning general, extensible and light-weight framework

  Language:Python8119

• wanglun1996/secure-robust-federated-learning

  Language:Python535

• imperial-qore/TranAD

  [VLDB'22] Anomaly Detection using Transformers, self-conditioning and adversarial training.

  Language:Python521158

• omarfoq/knn-per

  Official code for "Personalized Federated Learning through Local Memorization" (ICML'22)

  Language:Python4215

• AIoT-MLSys-Lab/FedRolex

  [NeurIPS 2022] "FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction" by Samiul Alam, Luyang Liu, Ming Yan, and Mi Zhang

  Language:Python6015

• shaoxiongji/federated-learning

  A PyTorch Implementation of Federated Learning http://doi.org/10.5281/zenodo.4321561

  Language:Python1.3k367

• NUAA-SmartSensing/FedModule

  联邦学习模块化框架，支持各类FL。A universal federated learning framework, free to switch thread and process modes

  Language:Python14820

• akhilmathurs/orchestra

  Source code for the ICML 2022 paper: "Orchestra: Unsupervised Federated Learning via Globally Consistent Clustering"

  Language:Python5310

• mit-han-lab/amc

  [ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices

  Language:Python428114

• vaseline555/SuPerFed

  (SIGKDD 2022) Connected Low-Loss Subspace Learning for a Personalization in Federated Learning (https://arxiv.org/abs/2109.07628)

  Language:Python284

• youngfish42/Awesome-FL

  Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)

  Language:Python1.5k186

• zhuangdizhu/FedGen

  Code and data accompanying the FedGen paper

  Language:Python23970

• bibikar/feddst

  Federated Dynamic Sparse Training

  Language:Python2911

• Shiweiliuiiiiiii/In-Time-Over-Parameterization

  [ICML 2021] "Do We Actually Need Dense Over-Parameterization? In-Time Over-Parameterization in Sparse Training" by Shiwei Liu, Lu Yin, Decebal Constantin Mocanu, Mykola Pechenizkiy

  Language:Python466

• RAIVNLab/STR

  Soft Threshold Weight Reparameterization for Learnable Sparsity

  Language:Python8811