Nemotron-RL-Identity-Following-v1

## Dataset Description: This synthetic dataset uses human created seed data to create a bank of prompts which probes a model's identity information: which company created it, and its official name and version number. This dataset is released as part of NVIDIA [NeMo Gym](https://github.com/NVIDIA-NeMo/Gym), a framework for building reinforcement learning environments to train large language models. NeMo Gym contains a growing collection of training environments and datasets to enable Reinforcement Learning from Verifiable Reward (RLVR). This dataset was utilized in the development of the [NVIDIA Nemotron](https://www.nvidia.com/en-us/ai-data-science/foundation-models/nemotron/) family of models. NeMo Gym is an open-source library within the [NVIDIA NeMo framework](https://github.com/NVIDIA-NeMo/), NVIDIA's GPU-accelerated, end-to-end training framework for large language models (LLMs), multi-modal models, and speech models. This dataset is part of the https://huggingface.co/collections/nvidia/nemo-gym/ collection This dataset is ready for commercial use. ## Dataset Owner(s): NVIDIA Corporation ## Dataset Creation Date: 03/11/2026 ## License/Terms of Use: Governing Terms: This dataset is licensed under Creative Commons Attribution 4.0 International. ## Intended Usage: To be used with [NeMo Gym](https://github.com/NVIDIA-NeMo/Gym) for post-training LLMs. ## Dataset Characterization * Data Collection Method<br> * [Synthetic] <br> * Labeling Method<br> * [Human] <br> ## Dataset Format Text Only, compatible with https://huggingface.co/collections/nvidia/nemo-gym ## Dataset Quantification Record Count: 21660 Feature Count: 4 Total Data Storage: 8.2 MB ## Reference(s): [NeMo Gym](https://github.com/NVIDIA-NeMo/Gym) ## Ethical Considerations: NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal teams to ensure this dataset meets requirements for the relevant industry and use case and addresses unforeseen product misuse. Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).