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djlougen/busybee-cpu
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I am using HermesAgent-20 and want to reduce API calls. Walk me through setting up busybee-cpu as a local model endpoint so it handles routine decisions like reading files and running tests.
Help me train the busybee-cpu classifier on my own dataset of agent decision steps and evaluate its accuracy before deploying it as an endpoint.
How does busybee-cpu decide when to escalate to the language model instead of routing locally? Explain the confidence threshold and the escalate action logic.
I want to extend busybee-cpu to support a fifth action type beyond the current four. Show me how to add a new class to the classifier and retrain it.
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