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Related Questions
- What are the key strategies used in active learning to select the most informative samples for fine-tuning a text generation model?
- How does active learning help in reducing the labeling effort and cost associated with fine-tuning a large language model?
- What are the potential risks of using active learning in fine-tuning a text generation model, and how can they be mitigated?
- Can you explain the concept of 'uncertainty sampling' in active learning, and how it can be applied to fine-tuning a text generation model?
- How does active learning impact the quality and diversity of the training data for fine-tuning a text generation model?
- What are the differences between 'active learning' and 'transfer learning' in the context of fine-tuning a text generation model?
- How can active learning be used to adapt a pre-trained text generation model to a specific domain or task?
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