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Related Questions
- What are the primary factors that influence the size and quality of training data sets for large language models like Llama and Qwen?
- How does the size of the training data set impact the model's ability to generalize and handle out-of-distribution tasks?
- What are the trade-offs between increasing the size of the training data set and improving the quality of the data?
- How does the quality of the training data set affect the model's ability to capture nuances and context-dependent relationships in language?
- Can you provide examples of how Llama and Qwen's capabilities are impacted by their respective training data sets?
- How do the training data sets of Llama and Qwen compare in terms of diversity, representation, and coverage of different languages and domains?
- What are the implications of the trade-offs between data size and quality for the development of future large language models?
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