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Related Questions
- How can prompt engineering techniques be applied to create domain-specific language models that retain the flexibility of general-purpose models?
- What are some effective strategies for adapting general-purpose language models to specific domains, such as healthcare or finance?
- What are the key considerations when designing prompts for domain-specific language models to ensure they capture the nuances of the target domain?
- Can you elaborate on the role of metadata and context in bridging the knowledge gap between general-purpose and domain-specific language models?
- How can the limitations of general-purpose language models be addressed through the design of more targeted and informed prompts?
- What are some best practices for selecting the right level of specificity for prompts when adapting general-purpose language models to new domains?
- How can the integration of multiple knowledge sources and domain-specific data be used to enhance the performance of domain-specific language models?
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