Unified supervised fine-tuning (SFT) dataset of multi-turn chat examples focused on African history, colonial history, and related Q&A. Six public Hub chat datasets were normalized, concatenated, and deduplicated by conversation content into a single train split.
Rows: 26,897 · Split: train only · Format: chat (messages with role / content)
Artifacts (Parquet / JSONL / manifest): Svngoku/jobs-artifacts