Dataset formats¶
AReno loaders normalize external datasets into small dictionaries consumed by the selected algorithm. Keep tokenization out of the dataset layer; trainers own tokenizer rendering, sequence limits, and chat-template behavior.
SFT rows¶
SFT rows provide a supervised prompt and target response:
{"prompt": "Instruction: ...", "response": "..."}
DPO rows¶
DPO rows provide one shared prompt and two ranked answers:
{"prompt": "...", "chosen": "...", "rejected": "..."}
Prompt-based RL rows¶
GSPO, GRPO, and PPO prompt datasets provide prompt. They can also preserve
task metadata such as solutions for reward functions.
Agentic rows¶
Agentic datasets provide prompt plus any task metadata consumed by the agent
and reward files.
Where to go next¶
Dataset loaders documents loader shapes and examples.
Reward functions explains how preserved metadata is used for scoring.