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This process involves branching from a base model and training the branch on specific domain data in order to establish an expert, which routing logic is then able to activate in serving inference requests. The result is a framework for domain expertise that is easily-extensible, modular, and efficient.
Contents
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Prerequisites
M*DEL's Aurora model (aurora-m) will be used as the base and RunPod compute resources will be used for training. Also, Weights and Biases will collect information during training for monitoring status, evaluating progress, and to allow comparing subsequent training runs for performance.
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