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PyTorch implementation of 'Generative AI-Powered Plugin for Robust Federated Learning in Heterogeneous IoT Networks''

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Generative AI-Powered Plugin for Robust Federated Learning in Heterogeneous IoT Networks

This is an official implementation of the following paper:

Youngjoon Lee, Jinu Gong, and Joonhyuk Kang. Generative AI-Powered Plugin for Robust Federated Learning in Heterogeneous IoT Networks
arXiv preprint arXiv:2410.23824.

Requirements

Please install the required packages as below

pip install tensorboard scipy tqdm pandas torch ollama transformers

Federated Learning Techniques

This paper considers the following federated learning techniques

Edge AI Model

  • google-bert/bert-base-uncased
  • distilbert/distilbert-base-uncased
  • dmis-lab/biobert-v1.1
  • microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext

LLM

  • Gemma 1.0:7B, Gemma 2.0:2B/9B
  • Llama 3.1:8B, Llama 3.2:1B/3B
  • Phi 2.0:3B, Phi 3.0:3B, Phi 3.5:3B

Dataset

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PyTorch implementation of 'Generative AI-Powered Plugin for Robust Federated Learning in Heterogeneous IoT Networks''

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