How to Match LLM Patterns to Problems
Read OriginalThis technical article provides a framework for matching Large Language Model (LLM) patterns to specific production problems. It distinguishes between external and internal LLMs and categorizes patterns by their relationship to data. The guide addresses issues like lack of performance metrics, poor external model performance, and data constraints, recommending solutions such as evals, RAG, fine-tuning, and caching.
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