Federated Learning with Hugging Face and Flower: A Practical Guide
Research#Federated Learning📝 Blog|Analyzed: Jan 26, 2026 11:36•
Published: Mar 27, 2023 00:00
•1 min read
•Hugging FaceAnalysis
This article provides a practical tutorial on federated learning using Hugging Face and Flower, enabling fine-tuning of language models across distributed clients while preserving data privacy. It leverages the simulation functionality of Flower for local testing, showcasing a straightforward approach to a complex machine learning technique. The guide uses distilBERT for IMDB sentiment analysis, demonstrating a real-world application.
Key Takeaways
- •The tutorial demonstrates how to fine-tune a pre-trained Transformer model (distilBERT) for sequence classification using federated learning.
- •It uses the Flower framework to simplify the process of federating the training of language models across multiple clients.
- •The guide provides a complete code example within the Flower repository for easy implementation.
Reference / Citation
View Original"This tutorial will show how to leverage Hugging Face to federate the training of language models over multiple clients using Flower."