Alternatives and similar repositories for FeT

Users that are interested in FeT are comparing it to the libraries listed below

• 1xbq1 / FedMLLM
  ☆25Updated 2 months ago
• CERT-Lab / fed-sb
  Fed-SB: A Silver Bullet for Extreme Communication Efficiency and Performance in (Private) Federated LoRA Fine-Tuning
  ☆13Updated 3 months ago
• Xtra-Computing / VertiBench
  Feature partitioner by imbalance or correlation (ICLR 2024)
  ☆16Updated 4 months ago
• FLAIR-Community / Fling
  ☆46Updated 6 months ago
• houcharlie / PrE-Text
  Implementation for PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs
  ☆22Updated last year
• Xtra-Computing / FedSim
  A coupled vertical federated learning framework that boosts the model performance with record similarities (NeurIPS 2022)
  ☆27Updated 2 years ago
• ATP-1010 / FederatedLLM
  ☆79Updated 5 months ago
• Pengxin-Guo / FedSA-LoRA
  Selective Aggregation for Low-Rank Adaptation in Federated Learning [ICLR 2025]
  ☆34Updated last month
• Luckfort / CD
  [COLING'25] Exploring Concept Depth: How Large Language Models Acquire Knowledge at Different Layers?
  ☆78Updated 4 months ago
• NVlabs / PerAda
  Repo for the paper: PerAda: Parameter-Efficient Federated Learning Personalization with Generalization Guarantees (CVPR 2024)
  ☆19Updated 9 months ago
• jzhang538 / BadMerging
  [CCS 2024] "BadMerging: Backdoor Attacks Against Model Merging": official code implementation.
  ☆28Updated 9 months ago
• AI-secure / FLBenchmark-toolkit
  Federated Learning Framework Benchmark (UniFed)
  ☆49Updated last year
• pzp-dzd / FedPFT
  This is the official implementation of the IJCAI 2024 paper "FedPFT: Federated Proxy Fine-Tuning of Foundation Models".
  ☆22Updated last year
• microsoft / DPSDA
  Private Evolution: Generating DP Synthetic Data without Training [ICLR 2024, ICML 2024 Spotlight]
  ☆97Updated last week
• UCSC-VLAA / FedConv
  [TMLR'24] This repository includes the official implementation our paper "FedConv: Enhancing Convolutional Neural Networks for Handling D…
  ☆25Updated last year
• Xtra-Computing / FedOV
  Towards Addressing Label Skews in One-Shot Federated Learning (ICLR 2023)
  ☆17Updated last year
• hanruiqian / Awesome-Federated-LLM-Related-Works
  ☆18Updated last year
• justarter / E2URec
  Official Code for paper "Towards Efficient and Effective Unlearning of Large Language Models for Recommendation" (Frontiers of Computer S…
  ☆37Updated 10 months ago
• FengHZ / BAFFLE
  The official implement of paper "Does Federated Learning Really Need Backpropagation?"
  ☆23Updated 2 years ago
• CERT-Lab / lora-sb
  Initialization using Update Approximation is a Silver Bullet for Extremely Efficient Low-Rank Fine-Tuning
  ☆47Updated 3 months ago
• facebookresearch / where_to_begin
  Repo to reproduce results for Where to Begin? On the Impact of Pre-Training and Initialization in Federated Learning
  ☆25Updated 2 years ago
• google-research / DP-FTRL
  DP-FTRL from "Practical and Private (Deep) Learning without Sampling or Shuffling" for centralized training.
  ☆29Updated last week
• wizard1203 / FuseFL
  FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion (NeurIPS 2024 Spotlight)
  ☆12Updated 2 months ago
• llm-eff / FedPepTAO
  ☆31Updated last year
• Xtra-Computing / OEBench
  OEBench: Investigating Open Environment Challenges in Real-World Relational Data Streams (VLDB 2024)
  ☆13Updated 9 months ago
• allen4747 / Ferret
  This is the official implementation for the paper: Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models
  ☆13Updated 8 months ago
• LuckMonkeys / arxiv-daily
  🎓Automatically Update Distributed Learning Papers Daily using Github Actions (Update Every 12th hours)
  ☆35Updated this week
• ngc436 / awesome-vertical-federated-learning
  A curated list of advancements in Vertical Federated Learning, frameworks and libraries.
  ☆35Updated 4 months ago
• OngWinKent / Federated-Feature-Unlearning
  [NeurIPS 2024] Official implementation of the paper “Ferrari: Federated Feature Unlearning via Optimizing Feature Sensitivity"
  ☆17Updated 2 months ago
• LINs-lab / FedTHE
  [ICLR 2023] Test-time Robust Personalization for Federated Learning
  ☆54Updated last year