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.