Model Optimization in Microsoft Foundry: Deployment and Evaluations
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 [[{“value”:”Validate and launch your customized models seamlessly using Microsoft Foundry! In this installment, we tackle what happens after the training is complete. You’ll learn how to deploy fine-tuned models effectively, manage long-term inference costs, and rigorously evaluate your model’s performance post-training using a custom grader logic to ensure production-grade reliability.

00:03 Welcome and scenario
00:52 Post-training evaluation
01:20 Demo: Using a custom grader for evaluations
03:35 Cost management
05:50 Model deployment

Microsoft Foundry – https://aka.ms/foundry-ft
Foundry Finetuning Demos on GitHub – https://aka.ms/ft-demos
Azure OpenAI Fintuning Costs: https://aka.ms/aoai-ft-cost

Bethany Jepchumba, Twitter/X – https://twitter.com/bethanyjep
Bethany Jepchumba, LinkedIn – https://www.linkedin.com/in/bethany-jep/
Bethany Jepchumba, GitHub – https://github.com/bethanyjep”}]] Read More Microsoft Developer 

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By ali

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