Model Versioning for GenAI Quiz

5 questions • Pass: 70% • +25 pts

Quiz covering GenAI Deployment Strategies

Model Versioning for GenAI Quiz

5 questions | Pass: 70% | Earn 25 points

Questions in this quiz

A preview of the 5 questions covered. Start the quiz above to answer them, check your score, and read the explanations.

  1. 1

    What is the primary purpose of model versioning in a GenAIOps pipeline?

  2. 2

    When deploying a fine-tuned LLM, why is it recommended to use a Model Registry instead of simple file-naming conventions like 'model_v1_final'?

  3. 3

    In a GenAI context, which of the following should be considered a 'versioned artifact' alongside the model weights?

  4. 4

    Which strategy best supports a 'Canary Deployment' for a new version of a Generative AI application?

  5. 5

    When implementing immutable model versioning, what is the most significant risk of 'overwriting' a model artifact in storage (e.g., saving over 'model.bin' without a version tag)?