模型微调与适配

题集来源:AMIT SHEKHAR(amitshekhariitbhu)收录项目:ai-engineering-interview-questions查看原题集

题目目录

32 道原题
  1. What is continual pre-training, and when would you use it?

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  2. How do you merge multiple LoRA adapters?

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  3. What is the difference between SFT (Supervised Fine-Tuning) and alignment training?

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  4. What is RLAIF (RL from AI Feedback), and how does it differ from RLHF?

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  5. What is Constitutional AI, and how does it differ from RLHF?

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  6. What is RLVR (Reinforcement Learning with Verifiable Rewards), and when does it beat a learned reward model?

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  7. What is knowledge distillation for fine-tuning, and what are the legal considerations?

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  8. Your fine-tuned LLM produces factually wrong outputs due to training data quality issues. How do you fix it?

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  9. You must choose between LoRA and full fine-tuning for a domain-specific assistant. How do you decide?

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  10. Your fine-tuned model memorized training data verbatim instead of learning patterns. How do you fix overfitting?

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