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Related Questions
- What are the key factors that contribute to the quality of a pre-training dataset?
- How does the size of the pre-training dataset affect the model's ability to generalize to out-of-distribution data?
- Can a smaller pre-training dataset still produce a well-generalizing model if it is carefully curated and diverse?
- What are some common pitfalls to avoid when creating a pre-training dataset for a large language model?
- How does the quality of the pre-training dataset impact the model's ability to learn from few-shot learning scenarios?
- Can a model trained on a high-quality pre-training dataset still suffer from poor generalizability if it is fine-tuned on a biased dataset?
- What are some strategies for evaluating the generalizability of a large language model to real-world data?
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