Recent content by clarakoala

When working with Model Training & Fine-Tuning, the biggest gains usually come from treating it as a repeatable workflow rather than a one-off prompt or experiment. One important area is data quality. Define what a good result looks like before changing tools or settings, then test one variable...

A useful way to look at Local LLMs explained: a practical look at setup choices is to focus first on local and llms. That tends to make the trade-offs easier to compare. It also gives you a cleaner baseline if you want to compare tools or settings later.