training-data

Use when assembling or curating the corpus a fine-tune trains on — turning raw examples into the JSONL shape a trainer expects (instruction, conversational, preference-pair or binary-label), matching the data to the model's chat template, generating synthetic or distilled examples, deduplicating and decontaminating against eval sets, and quality-filtering. NOT cleaning tabular rows, nulls and dtypes (that is…