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Related Questions
- What are the common methods used to handle out-of-vocabulary (OOV) words in NLP text classification tasks?
- How does Infermatic.ai's NLP pipeline handle OOV words during the tokenization process?
- What role does subwording and wordpiece tokenization play in handling OOV words in text classification tasks?
- Can you explain the concept of fine-tuning language models on specific tasks to improve their handling of OOV words?
- In what ways can pre-training language models on large-scale datasets help improve their handling of OOV words?
- How do techniques like named entity recognition (NER) and entity disambiguation affect the handling of OOV words in text classification?
- What is the impact of using multilingual language models on handling OOV words in cross-lingual text classification tasks?
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