Exploring Model Landscape and Implementing Base Models

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When navigating different models in the ML landscape, considering their support, licensing, MLOP infrastructure, and optimization toolkits is essential. While numerous new models are introduced regularly, focusing on selecting a base model with strong performance on similar data to the one you work with can streamline the fine-tuning process. It's recommended to refer to up-to-date leaderboards to identify the best-performing models for your specific use case before starting the fine-tuning process.

The new open source AI book from PremAI starts with “As a data scientist/ML engineer/developer with a 9 to 5 job, it’s difficult to keep track of all the innovations.” We couldn’t agree more, and we are so happy that this week’s guest Casper (among other contributors) have created this resource for practitioners.

During the episode, we cover the key categories to think about as you try to navigate the open source AI ecosystem, and Casper gives his thoughts on fine-tuning, vector DBs & more.

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