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Congratulations on completing the course. In this course, you've learned about the potential of leveraging private data, using federated learning to make LLMs even smarter. In particular, you've learned about how this method can help you manage key privacy and efficiency issues that come up when combining federated learning and LLMs together. So now that you've got a start down this path of LLMs and Federated learning, what is next? You can find a lot more on this topic. New recipes, new approaches. Examples by visiting Flower dot AI or following us flwrlabs at x.com, or join thousands of like minded AI researchers and engineers at the Flower community slack. I would also recommend more specifically, you look at Flower Tune, the Flower Tune leaderboard, and our new album Pre-trained Technology called Flower LLM. And lastly, thank you to the incredible Flower community. I'm excited to see the amazing examples of federated LLMs soon to be built by you all.
course detail
Next Lesson
Federated Fine-tuning of LLMs with Private Data
  • Introduction
    Video
    ・
    3 mins
  • Smarter LLMs with Private Data
    Video
    ・
    11 mins
  • Centralized LLM Fine-tuning
    Video with Code Example
    ・
    16 mins
  • Federated Fine-tuning for LLMs
    Video with Code Example
    ・
    41 mins
  • Keeping LLMs Private
    Video with Code Example
    ・
    34 mins
  • Conclusion
    Video
    ・
    1 mins
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