What's the hardest part of creating edge cases for fine-tuning open-weight models? [D]

Overview

I'm interested in how people build datasets for fine-tuning open-weight models, especially when it is about making a model handling edge cases than just perform well on common examples. I'm curious about the data side of the process. Finding edge cases: How do you identify edge cases that are rare or unusual. Also how do you make edge cases on an existing dataset to make it more specialized for what you need. Generating examples: Do you write them by yourself, or use a good model to gene

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