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Related Questions
- How do language models handle out-of-vocabulary (OOV) words during training and inference?
- What is the impact of OOV word handling on the overall performance and accuracy of language models?
- Can you explain the relationship between model complexity and the ability to handle OOV words in language models?
- How do different OOV handling techniques, such as subword modeling or character-level modeling, affect model complexity?
- What are the trade-offs between using a large vocabulary and a simpler model versus using a smaller vocabulary and a more complex model?
- How do OOV handling and model complexity interact with other factors, such as the size of the training dataset and the choice of optimizer?
- Can you discuss the implications of OOV handling and model complexity for the deployment of language models in real-world applications?
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