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Related Questions
- What are the key differences between fine-tuning and general language understanding in large language models?
- How does fine-tuning impact the model's ability to adapt to new domains or tasks?
- Can you explain the trade-offs between fine-tuning and general language understanding in terms of model performance and data efficiency?
- How does the choice of fine-tuning or general language understanding affect the model's ability to handle out-of-vocabulary words or concepts?
- What are some best practices for selecting between fine-tuning and general language understanding in different applications?
- Can you discuss the role of transfer learning in fine-tuning and its impact on the model's ability to generalize to new data?
- How does the level of fine-tuning (e.g., task-specific vs. domain-specific) influence the model's ability to generalize to new data?
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