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Related Questions
- How does pre-training on large datasets impact a model's ability to generalize to different domains?
- Can you explain the concept of 'domain adaptation' in the context of large language models?
- What are some common challenges that arise when adapting a pre-trained model to a new domain?
- How does the size and quality of the pre-training dataset affect a model's ability to adapt to new tasks?
- Can you discuss the relationship between pre-training on a diverse dataset and a model's ability to handle out-of-distribution inputs?
- How do techniques like transfer learning and fine-tuning contribute to a model's ability to adapt to new tasks and domains?
- What are some strategies for adapting a pre-trained model to a new domain, and what are their trade-offs?
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