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Related Questions
- What are the key differences between few-shot and few-example learning for adapting large language models to new domains?
- How can transfer learning and domain adaptation techniques be applied to fine-tune large language models for specific tasks?
- What role does data augmentation play in adapting large language models to new domains or tasks?
- What are some common challenges in adapting large language models to new domains or tasks, and how can they be addressed?
- Can you explain the concept of meta-learning and its applications in adapting large language models to new domains or tasks?
- How can multi-task learning be used to adapt large language models to multiple related tasks or domains?
- What are some best practices for selecting and preparing data for adapting large language models to new domains or tasks?
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