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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