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Related Questions
- What factors contribute to a pre-training dataset's ability to support a model's adaptability to new domains?
- In what ways can a larger pre-training dataset improve a model's ability to generalize to new domains?
- How does the diversity and representativeness of the pre-training dataset impact the model's adaptability to new domains?
- What are the trade-offs between the size and quality of the pre-training dataset, and how do they impact the model's adaptability to new domains?
- Can a high-quality pre-training dataset with a smaller size be more effective than a larger but lower-quality dataset in supporting the model's adaptability to new domains?
- What are the implications of using a pre-training dataset that is biased or imbalanced on the model's ability to adapt to new domains?
- How can the pre-training dataset be designed or curated to support the model's adaptability to new domains, and what are the key considerations in doing so?
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