GENERATIVE-AI-ENGINEER-ASSOCIATE · Question #101
A Generative AI Engineer developed an LLM application using the pay-per-token Foundation Model API. Now that the application is ready to be deployed, they would like to ensure the model endpoint can s
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Question
A Generative AI Engineer developed an LLM application using the pay-per-token Foundation Model API. Now that the application is ready to be deployed, they would like to ensure the model endpoint can serve high incoming volumes of requests in production. What should the Generative AI Engineer consider?
Options
- ASwitch to using External Models instead
- BThrottle the incoming batch of requests manually to avoid rate limiting issues
- CChange to a model with a fewer number of parameters in order to reduce hardware constraint
- DDeploy the model using provisioned throughput as it comes with performance guarantees
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