Teknosys learning library

AI model development

Explore the model-development lifecycle: preparing datasets, selecting a base model, understanding training and fine-tuning, evaluating outputs, and integrating inference into real applications. Discuss approaches such as instruction tuning and parameter-efficient fine-tuning with LoRA, alongside the trade-offs between quality, compute, and deployment cost.

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