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Related Questions
- What are the trade-offs between model size and computational resources when fine-tuning a pre-trained language model for a specific task?
- How does the architectural complexity of a pre-trained model impact its ability to generalize to new, unseen data?
- Can you explain the relationship between the size of a pre-trained model and its capacity to capture long-range dependencies in text?
- How does the pre-training objective of a language model influence its performance on downstream tasks?
- Can you discuss the impact of model size on the interpretability of a pre-trained language model's predictions?
- What are the implications of using a pre-trained model with a large vocabulary on a task that requires a small vocabulary?
- How does the level of pre-training data influence the performance of a language model on out-of-domain tasks?
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