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

题目目录

80 道原题
  1. What is Grouped-Query Attention (GQA), and how does it differ from Multi-Head Attention (MHA)?

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  2. How does Sliding Window Attention work?

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  3. How do Attention Sinks work?

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  4. How does Rotary Position Embedding (RoPE) work, and why is it preferred over learned positional embeddings?

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  5. Explain Layer Normalization

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  6. Explain RMSNorm (Root Mean Square Layer Normalization)

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  7. Why do modern Transformers use Pre-LayerNorm (Pre-Norm) instead of Post-LayerNorm?

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  8. What are scaling laws (Chinchilla), and how do they guide model size vs training data decisions?

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  9. Your LLM keeps ignoring your instructions. How do you make it follow structured output formats?

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  10. Your LLM-powered tool hits the context window limit on long documents. How do you handle it?

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