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Related Questions
- What is the primary function of self-attention in large language models like Llama and Qwen?
- How does self-attention enable the model to capture long-range dependencies in the input sequence?
- Can you explain the difference between self-attention and traditional recurrent neural networks in handling long-range dependencies?
- How does the self-attention mechanism allow the model to weigh the importance of different input elements when computing the output?
- What are some common applications of self-attention in natural language processing tasks, and how does it improve model performance?
- How does the number of attention heads in self-attention affect the model's ability to capture complex relationships between input elements?
- Can you provide an example of how self-attention is used in a real-world NLP task, such as machine translation or text summarization?
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