An AutoML framework for automatically selecting the optimal Generative AI model and adaptation strategy (zero-shot, few-shot, RAG, fine-tuning) for a given task. Designed to benchmark, evaluate, and deploy the best-performing GenAI setup based on task requirements, cost, latency, and quality.
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An AutoML framework for automatically selecting the optimal Generative AI model and adaptation strategy (zero-shot, few-shot, RAG, fine-tuning) for a given task. Designed to benchmark, evaluate, and deploy the best-performing GenAI setup based on task requirements, cost, latency, and quality.
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mbaddar1/AutoGenie
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An AutoML framework for automatically selecting the optimal Generative AI model and adaptation strategy (zero-shot, few-shot, RAG, fine-tuning) for a given task. Designed to benchmark, evaluate, and deploy the best-performing GenAI setup based on task requirements, cost, latency, and quality.
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