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Related Questions
- What are the advantages of using pre-trained LLM models in prompt engineering?
- How does fine-tuning on specific tasks improve the performance of LLM models in prompt engineering?
- What are the potential drawbacks of relying solely on pre-trained LLM models in prompt engineering?
- Can you explain the concept of 'domain adaptation' in the context of fine-tuning LLM models for specific tasks?
- What are some common challenges associated with fine-tuning LLM models on specific tasks, and how can they be addressed?
- How do pre-trained LLM models and fine-tuning interact with the concept of 'prompt engineering'?
- What are some real-world applications where the trade-off between pre-trained LLM models and fine-tuning on specific tasks is particularly relevant?
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