Llama Maker

Llama Maker is a developer-focused tool to design, prototype, and evaluate LLaMA-based models and prompts. It standardizes the configuration workflow, enabling teams to specify model size, context window, data sources, prompt schemas, and evaluation metrics in a single, repeatable plan.
Conceptually, users provide inputs such as model_size, context_window, training_data_source, and evaluation_metrics, and the tool generates a ready-to-run prototype configuration, along with an evaluation plan and export artifacts. Outputs include a structured prototype_config, a traceable evaluation_results, and reproducible artifacts suitable for sharing or integration into training pipelines.
Audience includes ML engineers, data scientists, and research staff who iterate on model prompts, data curation, and evaluation strategies. Unique value lies in its explicit separation of required versus optional features, built-in evaluation hooks, data-policy gates, and reproducible export formats. Use cases cover prompt design experiments, small-scale fine-tuning planning, safety constraint checks, and governance-ready report artifacts.