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Related Questions
- What are the key differences between transfer learning and fine-tuning in the context of LLMs?
- How do pre-trained LLMs leverage transfer learning to adapt to new tasks with varying levels of similarity?
- Can you explain the concept of task similarity and how it affects the effectiveness of transfer learning in LLMs?
- What are some common challenges that LLMs face when adapting to new tasks with varying levels of similarity, and how can transfer learning and fine-tuning address these challenges?
- How do LLMs select the most relevant knowledge from a pre-trained model to adapt to a new task, and what role does fine-tuning play in this process?
- What are some best practices for applying transfer learning and fine-tuning techniques to LLMs, especially when dealing with tasks that have varying levels of similarity?
- Can you provide examples of successful applications of transfer learning and fine-tuning in LLMs, and what made them effective in adapting to new tasks with varying levels of similarity?
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