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Related Questions
- What are the key differences between domain adaptation and fine-tuning a large language model?
- How does a large language model's lack of domain-specific knowledge affect its performance in a new domain?
- What are some common strategies for adapting a large language model to a new domain, such as transfer learning or data augmentation?
- What are the trade-offs between adapting a pre-trained model versus training a new model from scratch?
- How does the quality and quantity of domain-specific data impact the effectiveness of domain adaptation?
- What are some common pitfalls to avoid when adapting a large language model to a new domain, such as overfitting or underfitting?
- How can we evaluate the success of domain adaptation and determine whether the model has indeed learned to generalize to the new domain?
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