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Description
A synthetic instruction-style question-answering dataset derived from the NIST Artificial Intelligence Risk Management Framework (AI RMF 1.0). It is designed to support training, fine-tuning, retrieval evaluation, and domain-specific question-answering use cases related to AI risk management, trustworthy AI, and responsible AI. The dataset was created by leeroy-jankins and was last updated on HuggingFace in May 2026.
Use Cases
Fine-tuning language models for domain-specific question answering based on AI risk management concepts.
Evaluating retrieval-augmented generation (RAG) systems on technical policy documents.
Training models to generate instructional responses related to trustworthy and responsible AI principles.
Benchmarking model performance on synthetic instruction-following tasks derived from a structured framework.
Strengths
Dataset is derived directly from the authoritative NIST AI RMF 1.0 framework.
Specifically designed for training and evaluating models on AI risk management topics.
Limitations
Dataset size, row count, and column definitions are unknown, limiting suitability assessment.
Description metadata is limited; actual data quality and structure require manual inspection after download.
The dataset is synthetic, which may limit its realism for certain evaluation scenarios.