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Related Questions
- What role does domain-specific training data play in shaping the performance of large language models like Llama and Qwen?
- How do the training data sets of Llama and Qwen impact their ability to handle specialized knowledge and terminology?
- What are some common challenges in creating high-quality training data sets for domain-specific knowledge, and how do Llama and Qwen address these challenges?
- Can you provide examples of domain-specific knowledge areas where Llama and Qwen have demonstrated strong performance, and what contributed to their success?
- How do the training data sets of Llama and Qwen affect their ability to generalize and apply domain-specific knowledge to new, unseen scenarios?
- What are some potential limitations of relying on domain-specific training data, and how do Llama and Qwen mitigate these limitations?
- Can you discuss the trade-offs between domain-specific training data and more general-purpose training data, and how Llama and Qwen balance these competing priorities?
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