nvidia/Nemotron-RL-Instruction-Following-Free-Form-Formatting-v1

Dataset Description:

Teaches the model to follow arbitrary text formatting instructions (bullet styles, numbering, delimiters, heading formats, inline emphasis, web-answer structure, etc.) for targeted chat behaviors. Uses explicit Regex and string matching for the reward signal.

This dataset is ready for commercial or non-commercial uses.

Dataset Owner(s):

NVIDIA Corporation

Dataset Creation Date:

Created on: April 10, 2026 Last Modified on: April 10, 2026

Version:

Nemotron-RL-Instruction-Following-Free-Form-Formatting-v1

License/Terms of Use:

Governing terms: this dataset is licensed under CC BY 4.0.

Intended Usage:

Reinforcement learning training for instruction following capabilities, especially in freeform text output formatting.

Dataset Characterization

Data Collection Method
Synthetic

Labeling Method Hybrid: Synthetic, Automatic

Dataset Format

Modality: Text
Format: JSONL
Structure: Text + Metadata

Dataset Quantification

Subset	Samples	Size
Mixed formatting constraints	1,664 (18.4%)	8.01 MB (0.008 GB)
Bullet/list formatting	1,426 (15.8%)	6.50 MB (0.006 GB)
Web-style sections/steps	1,371 (15.2%)	6.29 MB (0.006 GB)
Key-value formatting	1,350 (14.9%)	6.42 MB (0.006 GB)
Numbered-list formatting	1,295 (14.3%)	6.14 MB (0.006 GB)
Heading formatting	869 (9.6%)	4.21 MB (0.004 GB)
Table formatting	476 (5.3%)	2.24 MB (0.002 GB)
Delimiter/separator formatting	422 (4.7%)	1.92 MB (0.002 GB)
Inline text formatting	164 (1.8%)	0.75 MB (0.001 GB)
Total	9,037	42.47 MB (0.042 GB)

Reference(s):

Nemo-Gym config: https://github.com/NVIDIA-NeMo/Gym/blob/main/resources_servers/format_verification/configs/freeform_formatting.yaml

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. Developers should work with their internal developer teams to ensure this dataset meets requirements for the relevant industry and use case and addresses unforeseen product misuse.

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