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. Why did DPO displace PPO-based RLHF at many labs? When is online RL still better?

    原题
  2. What is instruction tuning, and why is it important for chat models?

    原题
  3. How do you prepare a dataset for fine-tuning an LLM?

    原题
  4. What is catastrophic forgetting, and how do you prevent it during fine-tuning?

    原题
  5. When should you choose fine-tuning over RAG over prompt engineering?

    原题
  6. How do you evaluate a fine-tuned model's performance?

    原题
  7. What is synthetic data generation, and how do you use it for fine-tuning?

    原题
  8. What are the key hyperparameters for fine-tuning (learning rate, epochs, batch size, LoRA rank)?

    原题
  9. Do the GPU memory math for full fine-tuning a 7B model in bf16 with Adam. Now with LoRA and QLoRA.

    原题
  10. How do you fine-tune a model for a specific domain (legal, medical, finance)?

    原题