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Related Questions
- Does subwording reduce the number of parameters in a language model, and if so, how does this affect training time and computational resources?
- How does the choice of subwording algorithm (e.g. WordPiece, BPE) impact the computational resources required for training a language model?
- Can you explain the trade-off between using subwording to reduce the vocabulary size and the potential loss of contextual information?
- How does subwording affect the model's ability to capture rare or out-of-vocabulary words?
- What are the implications of subwording on the model's ability to generalize to unseen data?
- Can you discuss the impact of subwording on the model's interpretability and explainability?
- How does the size of the subword vocabulary impact the model's performance and computational requirements?
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