使用 Hugging Face 與 Flower 進行聯邦學習（Federated Learning）
Original: Federated Learning using Hugging Face and Flower
As privacy awareness grows and regulatory requirements tighten, training machine learning models without centralizing sensitive data has…
本文介紹如何整合 Hugging Face 與開源聯邦學習框架 Flower，實現保護隱私的分散式模型訓練。透過 Flower，開發者可以在不共享原始數據的情況下，協同微調 Hugging Face 上的 Transformer 模型。文中提供具體的實作步驟，包含定義 Flower Client、設定伺服器聚合演算法（如 FedAvg）以及評估模型效能。
As privacy awareness grows and regulatory requirements tighten, training machine learning models without centralizing sensitive data has become a critical challenge in modern AI. Federated Learning (FL) emerged as a solution: it allows local training to occur on multiple decentralized clients, with only model weights or gradients sent to a central server for aggregation, thereby eliminating the risk of data leakage.
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