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Related Questions
- How do word embeddings models handle words that are not present in their training data?
- What techniques do word embeddings models use to represent out-of-vocabulary words?
- Can you explain the concept of subword modeling in relation to out-of-vocabulary words?
- How do word embeddings models handle rare or low-frequency words?
- What is the impact of out-of-vocabulary words on the performance of a language model?
- Are there any techniques to improve the handling of out-of-vocabulary words in word embeddings models?
- How do pre-trained word embeddings models handle out-of-vocabulary words when fine-tuned on a new task?
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