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Related Questions
- What is the key difference between pre-training and fine-tuning in the context of large language models?
- How do the capabilities of pre-trained and fine-tuned models vary, and what are the implications for their applications?
- Can you explain the concept of shared weights in pre-trained and fine-tuned models, and how it affects their performance?
- What are the primary advantages and disadvantages of using pre-trained models versus fine-tuning them for a specific task?
- How does the concept of transfer learning relate to pre-training and fine-tuning, and what benefits does it offer?
- In what scenarios is it more beneficial to use a pre-trained model versus a fine-tuned model, and vice versa?
- Can you provide examples of tasks where pre-trained and fine-tuned models have been shown to have distinct strengths and weaknesses?
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