大模型基础

题集来源:AMIT SHEKHAR(amitshekhariitbhu)收录项目:ai-engineering-interview-questions查看原题集 反馈(在 GitHub 新标签页打开)

题目目录

80 道原题
  1. Why is the context window limited in LLMs?

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  2. What is temperature in the context of LLMs, and how does it affect output?

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  3. Why is the first token slower than the rest in an LLM?

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  4. Explain Top-p (nucleus) sampling and Top-k sampling. How do they differ?

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  5. Compare greedy decoding, beam search, top-k, top-p, and temperature sampling. When does each fail?

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  6. What are logits, and how are they used in text generation?

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  7. What are stop tokens in LLMs, and how does an LLM know when to stop generating?

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  8. What is the difference between a stop token and a stop sequence?

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  9. What are skip connections (residual connections) in Transformers?

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  10. What is the difference between open-source and closed-source LLMs? When would you choose one over the other?

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