How to optimize

Some discussions on improving latency, costs, and output quality.

📄️ Chain-of-thought

Enable the model to 'think' before answering to improve accuracy on complex reasoning tasks.

Reduce prompt size and latency using compact type definitions and aliases.

Provide examples in the prompt to guide the model's format and logic.

Optimize output selection with decoding strategies like Greedy, Beam Search, and Min-P.

Decompose complex tasks into smaller subtasks for better reliability and performance.

Gracefully handle non-compliant inputs and errors from users and services.

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