How can federated learning be used to train Generative AI across distributed datasets

Question

With the help of code can you tell me How can federated learning be used to train Generative AI across distributed datasets?

Answer 1

Continuous Integration and Continuous Deployment (CI/CD) pipelines automate the training, testing, and deployment of Generative AI models. This ensures faster iteration, better reproducibility, and seamless updates in production.

Here is the code snippet you can refer to:

In the above code we are using the following key points:

• Automated Model Training: Every push triggers model training with the latest data.
• Dependency Management: Ensures correct Python and library versions are installed.
• Model Artifact Storage: Saves the trained model for deployment.
• Containerized Deployment: Uses Docker for easy scaling and reproducibility.
• Version Control: Each model update is tracked and versioned in GitHub.

Hence, by referring to above, you can train Generative AI across distributed datasets.