Explain the importance of tokenization in LLMs.

58

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What is the role of vector embeddings in Generative AI?

26

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What are the benefits and challenges of fine-tuning a pre-trained model?

33

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How do you decide whether to fine-tune or train a model from scratch?

37

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What is reinforcement learning with human feedback (RLHF), and how is it applied?

38

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How do you prevent overfitting during fine-tuning?

62

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What are some real-world applications of Generative AI?

43

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What metrics do you use to evaluate the performance of a fine-tuned model?

29

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What are the best practices for deploying Generative AI models in production?

41

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How do you optimize LLMs for low-latency applications?

29

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What challenges arise when scaling LLMs for large-scale usage?

57

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How do you integrate Generative AI models with existing enterprise systems?

29

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What is the role of containerization and orchestration in deploying LLMs?

35

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What metrics are used to evaluate the quality of generative outputs?

32

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How do you measure diversity and coherence in text generated by LLMs?

35

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