GENERATIVE-AI-ENGINEER-ASSOCIATE · Question #95
A Generative AI Engineer is creating an LLM-based application. The documents for its retriever have been chunked to a maximum of 512 tokens each. The Generative AI Engineer knows that cost and latency
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Question
A Generative AI Engineer is creating an LLM-based application. The documents for its retriever have been chunked to a maximum of 512 tokens each. The Generative AI Engineer knows that cost and latency are more important than quality for this application. They have several context length levels to choose from. Which will fulfill their need?
Options
- Acontext length 514; smallest model is 0.44GB and embedding dimension 768
- Bcontext length 2048: smallest model is 11GB and embedding dimension 2560
- Ccontext length 32768: smallest model is 14GB and embedding dimension 4096
- Dcontext length 32768: smallest model is 14GB and embedding dimension 4096
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