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Query documented hyperparameter values, ranges, and tuning heuristics. Returns a suggestion table with KB-grounded justification.

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When to Use

  • Default values: Look up recommended defaults for framework parameters
  • Tuning ranges: Get recommended ranges and tuning strategies
  • Context-specific settings: Suggestions tailored to hardware, model size, or task type

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Parameters

ParameterRequiredTypeDescription
queryYesstringHyperparameter question

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Example

Tool: query_hyperparameter_priors
Query: "Learning rate and LoRA rank for QLoRA fine-tuning Llama-3 8B"
Returns: A suggestion table with recommended values, ranges, and KB-grounded justification for each parameter.