datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Aegis-AI-Content-Safety-Dataset-2.0
🛡️ Nemotron Content Safety Dataset V2
The Nemotron Content Safety Dataset V2, formerly known as Aegis AI Content Safety Dataset 2.0, is comprised of 33,416 annotated interactions between humans and LLMs, split into 30,007 training samples, 1,445 validation samples, and 1,964 test samples. This release is an extension of the previously published Nemotron Content Safety Dataset V1.
To curate the dataset, we use the HuggingFace version of human preference data about harmlessness… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Aegis-AI-Content-Safety-Dataset-2.0.Aegis-AI-Content-Safety-Dataset-1.0
🛡️ Nemotron Content Safety Dataset V1
Nemotron Content Safety Dataset V1, formerly known as Aegis AI Content Safety Dataset, is an open-source content safety dataset (CC-BY-4.0), which adheres to Nvidia's content safety taxonomy, covering 13 critical risk categories (see Dataset Description).
Dataset Details
Dataset Description
Nemotron Content Safety Dataset V1 is comprised of approximately 11,000 manually annotated interactions between humans and LLMs, split… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Aegis-AI-Content-Safety-Dataset-1.0.Nemotron-Content-Safety-Audio-Dataset
Nemotron Content Safety Audio Dataset
Dataset Description
The Nemotron Content Safety Audio Dataset is a multimodal extension of the Nemotron Content Safety Dataset V2 (Aegis 2.0), comprising 1,928 audio files generated from the test set prompts. This dataset enables multimodal AI safety research by providing spoken versions of adversarial and safety-critical prompts across 23 violation categories.
LANGUAGE: All prompts are in English. However, the audio files were… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-Content-Safety-Audio-Dataset.Nemotron-3.5-Content-Safety-Dataset
Nemotron 3.5 Content Safety Dataset
Dataset Description:
Nemotron 3.5 Content Safety Dataset is a hybrid real/synthetic supervised instruction dataset for content-safety classification of human and assistant interactions. The dataset contains text-only and image-grounded single-turn conversations. Each example asks a classifier to determine user safety, response safety, and harmful categories; a subset also covers topic-following classification. Some training… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-3.5-Content-Safety-Dataset.Nemotron-Content-Safety-Reasoning-Dataset
Nemotron Content Safety Reasoning Dataset
The Nemotron Content Safety Reasoning Dataset contains reasoning traces generated from open source reasoning models to provide justifications for labels in two existing datasets released by NVIDIA: Nemotron Content Safety Dataset V2 and CantTalkAboutThis Topic Control Dataset. The reasoning contains justifications for labels of either stand-alone user prompts engaging with an LLM or pairs of user prompts and LLM responses that are either… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-Content-Safety-Reasoning-Dataset.Aegis-AI-Content-Safety-Dataset-2.0
🛡️ Nemotron Content Safety Dataset V2
The Nemotron Content Safety Dataset V2, formerly known as Aegis AI Content Safety Dataset 2.0, is comprised of 33,416 annotated interactions between humans and LLMs, split into 30,007 training samples, 1,445 validation samples, and 1,964 test samples. This release is an extension of the previously published Nemotron Content Safety Dataset V1.
To curate the dataset, we use the HuggingFace version of human preference data about harmlessness… See the full description on the dataset page: https://huggingface.co/datasets/jxhnathan/Aegis-AI-Content-Safety-Dataset-2.0.Aegis-AI-Content-Safety-Dataset-2.0
🛡️ Nemotron Content Safety Dataset V2
The Nemotron Content Safety Dataset V2, formerly known as Aegis AI Content Safety Dataset 2.0, is comprised of 33,416 annotated interactions between humans and LLMs, split into 30,007 training samples, 1,445 validation samples, and 1,964 test samples. This release is an extension of the previously published Nemotron Content Safety Dataset V1.
To curate the dataset, we use the HuggingFace version of human preference data about… See the full description on the dataset page: https://huggingface.co/datasets/Riswan-BluBridge/Aegis-AI-Content-Safety-Dataset-2.0.Aegis-AI-Content-Safety-Dataset-2.0
🛡️ Nemotron Content Safety Dataset V2
The Nemotron Content Safety Dataset V2, formerly known as Aegis AI Content Safety Dataset 2.0, is comprised of 33,416 annotated interactions between humans and LLMs, split into 30,007 training samples, 1,445 validation samples, and 1,964 test samples. This release is an extension of the previously published Nemotron Content Safety Dataset V1.
To curate the dataset, we use the HuggingFace version of human preference data about harmlessness… See the full description on the dataset page: https://huggingface.co/datasets/AlphaHacker1729/Aegis-AI-Content-Safety-Dataset-2.0.Aegis-AI-Content-Safety-Dataset-2.0
🛡️ Nemotron Content Safety Dataset V2
The Nemotron Content Safety Dataset V2, formerly known as Aegis AI Content Safety Dataset 2.0, is comprised of 33,416 annotated interactions between humans and LLMs, split into 30,007 training samples, 1,445 validation samples, and 1,964 test samples. This release is an extension of the previously published Nemotron Content Safety Dataset V1.
To curate the dataset, we use the HuggingFace version of human preference data about harmlessness… See the full description on the dataset page: https://huggingface.co/datasets/shannifnju/Aegis-AI-Content-Safety-Dataset-2.0.Aegis-AI-Content-Safety-Dataset-2.0
🛡️ Nemotron Content Safety Dataset V2
The Nemotron Content Safety Dataset V2, formerly known as Aegis AI Content Safety Dataset 2.0, is comprised of 33,416 annotated interactions between humans and LLMs, split into 30,007 training samples, 1,445 validation samples, and 1,964 test samples. This release is an extension of the previously published Nemotron Content Safety Dataset V1.
To curate the dataset, we use the HuggingFace version of human preference data about… See the full description on the dataset page: https://huggingface.co/datasets/ritatai727/Aegis-AI-Content-Safety-Dataset-2.0.Content-Moderation-and-Safety
🇰🇿 Content Moderation and Safety, Kazakh Context
Dataset Summary
Content Moderation and Safety (Profanity) Kazakh Context is a comprehensive dataset designed specifically to train Large Language Models (LLMs) in detecting, classifying, and mitigating toxic, aggressive, or unsafe text in the Kazakh language.
📊 Dataset Statistics
General Metrics
Metric
Count
Total Samples
17,827
Total Words (approx.)
1,674,638
Avg.… See the full description on the dataset page: https://huggingface.co/datasets/farabi-lab/Content-Moderation-and-Safety.Content_Moderation_and_Safety_Kazakh_Context
🇰🇿 Content Moderation and Safety Kazakh Context
Dataset Summary
Toxic Speech Analysis and Mitigation, Kazakh Context is an advanced AI Safety dataset designed to train Large Language Models (LLMs) to detect, deeply analyze, and constructively rewrite toxic or harmful speech in the Kazakh language.
📊 Dataset Statistics
General Metrics
Metric
Count
Total Samples
12,063
Total Words (approx.)
5,869,718
Avg. Words per… See the full description on the dataset page: https://huggingface.co/datasets/farabi-lab/Content_Moderation_and_Safety_Kazakh_Context.aegis-ai-content-safety-dataset-2.0_Qwen3-8Baegis-ai-content-safety-processedAegis-AI-Content-Safety-Dataset-2.0-Telugu-safetyAegis-AI-Content-Safety-Dataset-2.0-english-safetyAegis-AI-Content-Safety-Single_labelThis Dataset is constructed on nvidia/Aegis-AI-Content-Safety-Dataset-1.0.
Aegis-AI-Content-Safety-Dataset-2.0_Qwen3-8B_rssample_content_safety_test_datasample_content_safety_test_datasample_content_safety_test_data-llamastack