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Related Questions
- Can you explain the trade-offs of using existing web scrapers to gather in-domain data from public source web pages versus training large models from scratch with a smaller, curated dataset?
- How does the quality of existing web scrapers impact the overall performance of a large language model when used for training?
- In what scenarios would using existing web pages lead to noise in the model's output, and how can this be mitigated?
- Can you discuss the potential benefits of using existing web pages, such as increased diversity and coverage of the training data?
- How does the concept of 'in-domain' data relate to web scraping, and what are the implications for large language model training?
- Can you provide examples of how existing web scrapers can be used to gather high-quality, in-domain data for large language models?
- What are some potential pitfalls to watch out for when using existing web pages as training data, and how can they be addressed?
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