Dataset Descriptions

This dataset contains 29980 examples and is synthetically created to enhance model's capabilities to follow instructions precisely and to satisfy user constraints. The constraints are borrowed from the taxonomy in IFEval dataset. To generate diverse instructions, we expand the methodology in Ge et al., 2024 by using personas. More details and exact prompts used to construct the dataset can be found in our paper.

• Curated by: Allen Institute for AI
• Paper: TBD
• Repository: TBD
• Language(s) (NLP): English
• License: ODC-BY
• Point of Contact: Faeze Brahman

Loading

from datasets import load_dataset

dataset = load_dataset("allenai/tulu-3-sft-personas-instruction-following")["train"]

Dataset Structure

Each example in the dataset contains the standard instruction-tuning data points as follow:

• id (str): a unique identifier
• prompt (str): the verifiable instruction which involves satisfying 1 to 3 constraints
• messages (list): message format used for supervised fine-tuning (this contains user prompt and assistant response)
• constraints (list of str): a list of verifiable constraints that need to be satisfied by the assistant response