Federated Learning for LLMs.

Personalized Federated Learning with Moreau Envelopes (pFedMe) using Pytorch (NeurIPS 2020)

Implementation of dp-based federated learning framework using PyTorch

FedMD: Heterogenous Federated Learning via Model Distillation

AAAI 2024 accepted paper, FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning

Examples and guides for using the Gemini API.

The pytorch code of FedDISC (Federated Diffusion-Inspired Semi-supervised Co-training method)

Heterogeneous Federated Learning: State-of-the-art and Research Challenges

A native PyTorch Library for large model training

🎓Automatically Update Distributed Learning Papers Daily using Github Actions (Update Every 12th hours)

A federated image segmentation method based on style transfer

[ICLR 2024] "Enhancing One-Shot Federated Learning Through Data and Ensemble Co-Boosting"

TPAMI 2024 - Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark

The official Meta Llama 3 GitHub site

The official implantation of SGPT (CVPR2024)

[MICCAI2024] "FedFMS: Exploring Federated Foundation Models for Medical Image Segmentation". A framework for fine-tuning SAM (Segment Anything) in the federated learning paradigm for medical image …

Global and Local Prompts Cooperation via Optimal Transport for Federated Learning

Awesome-LLM-Prompt-Optimization: a curated list of advanced prompt optimization and tuning methods in Large Language Models

[CVPR 2024] Official Repository for "FedSelect: Personalized Federated Learning with Customized Selection of Parameters for Fine-Tuning"

This is the official implementation of the IJCAI 2024 paper "FedPFT: Federated Proxy Fine-Tuning of Foundation Models".

ICLR 2024

CVPR 2024 accepted paper, An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning

Code for the paper "Pretrained Models for Multilingual Federated Learning" at NAACL 2022

✨✨Latest Advances on Multimodal Large Language Models