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Related Questions
- What are the primary factors that influence a language model's capacity, and how do they impact its performance?
- How do larger model capacities affect the computational resources required for training and inference?
- Can you explain the concept of 'capacity' in the context of machine learning models, and how it relates to their ability to learn and generalize?
- What are the trade-offs between increasing model capacity and improving model performance in terms of accuracy and robustness?
- How does the choice of model architecture and hyperparameters impact the optimal capacity for a given task or problem?
- Can you discuss the relationship between model capacity and the risk of overfitting, and how to mitigate this risk through regularization and other techniques?
- What are some strategies for efficiently scaling up model capacity to handle large datasets and complex tasks, while minimizing the associated computational costs?
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