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Related Questions
- How does the attention mechanism in LLMs help the model to distinguish between relevant and irrelevant information?
- Can you elaborate on the different types of attention mechanisms used in LLMs, such as self-attention and multi-head attention?
- How does attention in LLMs impact the model's ability to handle long-range dependencies and contextual relationships in the input data?
- What are some common challenges associated with training attention-based LLMs, and how can they be addressed?
- Can you provide an example of how attention is used in a real-world NLP application, such as text summarization or question answering?
- How does the attention mechanism interact with other components of the LLM, such as the encoder and decoder?
- Can you discuss the relationship between attention and the model's capacity to learn hierarchical representations of input data?
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