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Related Questions
- What are the primary applications of general-purpose NLP models compared to domain-specific models?
- How do domain-specific models adapt to specific domains and tasks, and what are the benefits of this adaptation?
- What are some common challenges faced by general-purpose NLP models when applied to specific domains, and how can they be addressed?
- Can you provide examples of successful domain-specific NLP models and their applications in real-world scenarios?
- How do domain-specific models handle out-of-domain data, and what techniques are used to mitigate this issue?
- What are the key differences in training data requirements between general-purpose and domain-specific NLP models?
- How do domain-specific models leverage domain knowledge and expertise to improve performance, and what are the implications for model development?
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