Anthropic C4

Google C7 (Gemini CLI)

LandingAI C1

Build with Andrew

Nvidia C2

Smarter LLMs with Private Data

Introduction

Federated Fine-tuning for LLMs

Conclusion

Centralized LLM Fine-tuning

Keeping LLMs Private

Quiz

Federated Fine-tuning of LLMs with Private Data

Learn how to securely fine-tune large language models (LLMs) with private data using federated methods, enhancing data privacy, minimizing risks of data leakage, and optimizing efficiency through Parameter-Efficient Fine-Tuning (PEFT) and Differential Privacy.

Flower Labs

#ffffff