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Related Questions
- What are the benefits and drawbacks of task-specific knowledge versus general knowledge in fine-tuning large language models for a particular domain?
- How does the trade-off between task-specific knowledge and general knowledge impact the performance of a fine-tuned language model?
- Can you explain the concept of 'domain adaptation' in the context of fine-tuning large language models and how it relates to the trade-off between task-specific knowledge and general knowledge?
- What are some common techniques used to balance task-specific knowledge and general knowledge in fine-tuning large language models for a particular domain?
- How does the size and complexity of the fine-tuning dataset impact the trade-off between task-specific knowledge and general knowledge?
- Can you discuss the role of pre-training and fine-tuning in shaping the trade-off between task-specific knowledge and general knowledge in large language models?
- What are some potential risks or pitfalls of prioritizing task-specific knowledge over general knowledge in fine-tuning large language models, and how can they be mitigated?
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