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In the previous chapter, we looked at the main use cases of Large Language Models using relatively simple models. However, to tackle truly serious problems, there are far more powerful models available that can solve complex tasks out of the box. Understanding how to select the right model for a specific task based on available resources, as well as how to execute it correctly, can ensure up to a 90% success rate in solving most tasks. Many NLP problems are typical, and in many cases, it is possible to find a model that can successfully handle the task at hand.

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LLM Internals and Evaluation

  • 章节

  • 发表日期：

    2025年

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  • Ivan Gridin

摘要

In the previous chapter, we looked at the main use cases of Large Language Models using relatively simple models. However, to tackle truly serious problems, there are far more powerful models available that can solve complex tasks out of the box. Understanding how to select the right model for a specific task based on available resources, as well as how to execute it correctly, can ensure up to a 90% success rate in solving most tasks. Many NLP problems are typical, and in many cases, it is possible to find a model that can successfully handle the task at hand.