chenxingqiang/PFLoRA-lib
PFLoRA-lib: Personalized Federated Learning with LoRA Algorithm Library focusing on privacy-protection, federated-learning, Citation, Extensibility, Supported A
This library helps machine learning researchers evaluate and compare different federated learning algorithms, especially those that personalize models while protecting data privacy. It takes various datasets (like medical images or text) and different federated learning algorithms as input, producing performance metrics and insights into how well models learn collaboratively without sharing raw data. Researchers and data scientists working on distributed machine learning problems in sensitive domains would find this useful.
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Use this if you are a researcher or data scientist evaluating personalized federated learning algorithms and need a robust platform for testing and comparing their performance with an emphasis on privacy and efficiency.
Not ideal if you need a production-ready federated learning system for deploying models directly to edge devices or a simple tool for basic centralized machine learning tasks.
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Language
Python
License
GPL-2.0
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Last pushed
Sep 19, 2024
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