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Related Questions
- What is the primary goal of pre-training in LLMs and how does it impact their contextual understanding?
- Can you explain the difference between pre-training and fine-tuning in LLMs, and why is fine-tuning necessary for contextual understanding?
- How does the size and complexity of the pre-training dataset affect the contextual understanding of LLMs?
- What are some common techniques used for fine-tuning LLMs to improve their contextual understanding, and how do they work?
- How does the choice of pre-training objective (e.g., masked language modeling, next sentence prediction) impact the contextual understanding of LLMs?
- Can you discuss the role of self-supervised learning in pre-training LLMs and its implications for contextual understanding?
- How do LLMs adapt to domain-specific knowledge and language during fine-tuning, and what are the key factors that influence this adaptation?
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