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Related Questions
- How does transfer learning improve the performance of a CNN-based LLM on image classification tasks?
- What are the key differences between fine-tuning and feature extraction in transfer learning for a transformer-based LLM?
- Can you provide an example of how pre-trained language models can be fine-tuned for a specific domain, such as medical text classification?
- How does the architecture of a pre-trained CNN-based LLM impact its ability to be fine-tuned for a new task?
- What are the benefits and limitations of using transfer learning for a transformer-based LLM on a large-scale text classification task?
- Can you explain the concept of 'feature reuse' in the context of transfer learning for LLMs, and provide an example of how it can be applied?
- How does the choice of pre-training task affect the performance of a transformer-based LLM when fine-tuning for a new task?
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