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Related Questions
- What are the key components of a large language model's architecture, and how do they contribute to its performance?
- How does the number of layers and parameters in an LLM affect its ability to capture long-range dependencies in language?
- What is the role of attention mechanisms in LLMs, and how do they impact training time and performance?
- How do LLMs with different tokenization schemes, such as word-piece or subword tokenization, affect their performance and training time?
- What is the impact of pre-training and fine-tuning on the performance and training time of an LLM?
- How do LLMs with different optimization algorithms, such as Adam or SGD, affect their training time and convergence?
- What is the relationship between the size of the LLM's vocabulary and its performance on out-of-vocabulary words?
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