AI output can be effectively tuned with the fine control parameters provided by the Groq Code CLI:
- Temperature Coefficient Adjustment: Use
-tParameters (0-2 range), technical documentation suggests 0.3-0.7 to maintain rigor, creative coding available 1.2-1.5 - Model Selection Strategy:: Adoption
/modelCommand to switch between different specialized models, e.g. code-specific modelsmixtral-8x7b-32768 - chain of thought explicitly: Open
/reasoningCommands allow AI to show the derivation process and facilitate verification of the logic - System Command Enhancement:: For example
groq -s '给出ES6版本实现并解释每一步'
For complex tasks, it is recommended to use the 'step-by-step questioning method': first ask the AI to plan the steps of the solution, and then realize it in stages. In conjunction with/clearcommand can reset the dialog context at any time to avoid message overload.
This answer comes from the articleGroq Code CLI: a customizable command line programming tool powered by GroqThe
May not be reproduced without permission:AI productivity tools " Optimizing Output Quality and Relevance of AI Code Generation Models
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