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Related Questions
- What are the primary characteristics of general-purpose NLP models and their training data?
- How do domain-specific NLP models differ from general-purpose models in terms of training data?
- What are the key considerations for selecting and preparing training data for domain-specific NLP models?
- Can you explain the concept of 'domain adaptation' in NLP and its relation to training data?
- How does the size and quality of training data impact the performance of general-purpose vs. domain-specific NLP models?
- What are some common challenges in collecting and preprocessing training data for domain-specific NLP models?
- How can we leverage transfer learning and multi-task learning to improve the performance of domain-specific NLP models with limited training data?
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