Data Annotator
Training an LLM entails a complex, multi-stage process beginning with the collection and meticulous curation of petabytes of diverse text data. The core involves an intensive pre-training phase, where the model learns statistical patterns and relationships by predicting masked words or the next sentence across this vast dataset. This is often followed by fine-tuning, which adapts the model for specific tasks or aligns it better with human instructions and values.