Creating a specialized Large Language Model (LLM) tailored to understand your custom data requires a strategic approach. This guide outlines four key techniques for building a specialized LLM, ranked from the simplest to the most complex and resource-intensive.

1. Prompting: The Simplest Approach

2. Retrieval-Augmented Generation (RAG): Adding Context to Prompts

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3. LoRA: Efficient Fine-Tuning

4. Full Fine-Tuning: The Comprehensive Solution

By understanding these techniques and their trade-offs, you can effectively create a specialized LLM tailored to your custom data needs.

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