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Related Questions
- How does model capacity impact the ability of a large language model (LLM) to generalize to unseen data?
- What is the optimal relationship between model capacity and training data size for achieving good generalization performance in LLMs?
- Can you explain the concept of 'capacity' in the context of LLMs and how it relates to overfitting and underfitting?
- How does the size of the training dataset affect the capacity of an LLM to generalize to new, unseen data?
- Can you provide examples of how different model capacities and training data sizes can lead to varying levels of generalization performance in LLMs?
- What are some common techniques used to increase the capacity of an LLM while maintaining or reducing the size of the training dataset?
- How does the relationship between model capacity and training data size impact the ability of an LLM to learn from few-shot learning tasks?
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