datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Nemotron-AIQ-Agentic-Safety-Dataset-1.0
Nemotron-AIQ Agentic Safety Dataset
Dataset Summary
Nemotron-AIQ-Agentic-Safety-Dataset is a comprehensive dataset that captures a broad range of novel safety and security contextual risks that can emerge within agentic systems. It highlights the robustness of NVIDIA's open model, llama-3.3-nemotron-super-49b-v1, when deployed as a research assistant inside AIQ, demonstrating its ability to handle a diverse spectrum of agentic safety and security challenges. The dataset… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-AIQ-Agentic-Safety-Dataset-1.0.Nemotron-AIQ-Agentic-Safety-Dataset-1.0
Nemotron-AIQ Agentic Safety Dataset
Dataset Summary
Nemotron-AIQ-Agentic-Safety-Dataset is a comprehensive dataset that captures a broad range of novel safety and security contextual risks that can emerge within agentic systems. It highlights the robustness of NVIDIA's open model, llama-3.3-nemotron-super-49b-v1, when deployed as a research assistant inside AIQ, demonstrating its ability to handle a diverse spectrum of agentic safety and security challenges. The dataset… See the full description on the dataset page: https://huggingface.co/datasets/yuqing1207/Nemotron-AIQ-Agentic-Safety-Dataset-1.0.agentic-publication-protocol-dataset
APP compare-app benchmark
Paired reader conversations and blinded evaluations comparing an Agentic
Publication Protocol (APP) paper agent against a general repository-aware
agent, on 11 quantum-physics papers.
For each paper, a neutral reader asks the same scripted questions to both agents;
the two transcripts are anonymized and scored by a blinded evaluator on
accuracy, informativeness, grounding, and honesty (1-10).
Evaluator: Codex CLI, gpt-5.5, reasoning effort xhigh… See the full description on the dataset page: https://huggingface.co/datasets/phynics/agentic-publication-protocol-dataset.hendar-agentic-ai-dataset
Hendar Agentic AI Evaluation & Security Benchmark
A compact, expert-authored benchmark for evaluating trustworthy agentic AI systems across capability, tool use, retrieval, security, policy enforcement, multi-agent coordination and regression safety.
This dataset is a public companion to the Agentic AI Academy by Hendar Mawan, PhD. It is designed for evaluation, CI regression testing, red-team exercises and engineering education—not as a generic instruction-tuning corpus.… See the full description on the dataset page: https://huggingface.co/datasets/h0000w/hendar-agentic-ai-dataset.agentic_coding_dataset
Agentic Coding Dataset
This dataset is a compilation of various coding and instruction-following datasets, designed to train agentic coding models.
Sources
This dataset aggregates samples from the following sources:
CodeAlpaca-20k
Instruction-following coding tasks.
Evol-CodeAlpaca-v1
Complex evolved coding instructions (WizardCoder style).
Code Review Instruct
Python code review, critique, and revision examples.
APPS (Automated Programming Progress Standard)… See the full description on the dataset page: https://huggingface.co/datasets/ethanker/agentic_coding_dataset.Nemotron-AIQ-Agentic-Safety-Dataset-1.0
Nemotron-AIQ Agentic Safety Dataset
Dataset Summary
Nemotron-AIQ-Agentic-Safety-Dataset is a comprehensive dataset that captures a broad range of novel safety and security contextual risks that can emerge within agentic systems. It highlights the robustness of NVIDIA's open model, llama-3.3-nemotron-super-49b-v1, when deployed as a research assistant inside AIQ, demonstrating its ability to handle a diverse spectrum of agentic safety and security challenges. The dataset… See the full description on the dataset page: https://huggingface.co/datasets/supraja04/Nemotron-AIQ-Agentic-Safety-Dataset-1.0.Nemotron-AIQ-Agentic-Safety-Dataset-1.0
Nemotron-AIQ Agentic Safety Dataset
Dataset Summary
Nemotron-AIQ-Agentic-Safety-Dataset is a comprehensive dataset that captures a broad range of novel safety and security contextual risks that can emerge within agentic systems. It highlights the robustness of NVIDIA's open model, llama-3.3-nemotron-super-49b-v1, when deployed as a research assistant inside AIQ, demonstrating its ability to handle a diverse spectrum of agentic safety and security challenges. The… See the full description on the dataset page: https://huggingface.co/datasets/meet-the-1337/Nemotron-AIQ-Agentic-Safety-Dataset-1.0.telecom-agentic-dataset
Telecom Agentic AI Dataset
A high-quality synthetic dataset of 2000 multi-turn conversations for training AI agents specialized in telecom network operations. Generated using Qwen3-32B served via vLLM on AMD MI300X.
📊 Dataset Stats
Metric
Value
Total samples
2,000
Format
ChatML (system/user/assistant)
Size
12.8 MB
Avg turns per conversation
3-6
Domains covered
7
Generation model
Qwen3-32B
Generation infra
vLLM on AMD MI300X
Generation… See the full description on the dataset page: https://huggingface.co/datasets/shaunak1234/telecom-agentic-dataset.how-agentic-m1-research-data
How Agentic M1 Research Data
Training and validation data used for the M1-stage 500M-parameter
How Agentic research model.
Files
pretrain/m1_pretrain_5b_clean_train.jsonl.gz: cleaned pretraining split.
pretrain/m1_pretrain_5b_clean_val.jsonl.gz: pretraining validation split.
pretrain/m1_pretrain_5b_clean_report.json: corpus construction and quality report.
pretrain/m1_pretrain_5b_clean_rejected_sample.jsonl.gz: a small sample of rejected records for auditing.… See the full description on the dataset page: https://huggingface.co/datasets/jjyaoao/how-agentic-m1-research-data.agentic-publication-protocol-dev-data
APP compare-app benchmark
Paired reader conversations and blinded evaluations comparing an Agentic
Publication Protocol (APP) paper agent against a general repository-aware
agent, on 11 public quantum-physics papers. This is the public-paper
subset reported in the APP paper's compare-app table.
For each paper, a neutral reader asks the same scripted questions to both agents;
the two transcripts are anonymized and scored by a blinded evaluator on
accuracy, informativeness… See the full description on the dataset page: https://huggingface.co/datasets/LionSR/agentic-publication-protocol-dev-data.toucan-agentic-thinking
Toucan Agentic with Thinking Dataset
This dataset contains agentic reasoning responses generated by MiniMax-M2.1 based on questions from Agent-Ark/Toucan-1.5M_SFT.
Dataset Description
For each user question, the model generates:
Thinking process: The model's reasoning wrapped in <think> tags
Response: A complete, helpful answer in natural language
The original tool definitions are preserved in the tools field for reference.
Statistics
Split
Examples… See the full description on the dataset page: https://huggingface.co/datasets/agent-data/toucan-agentic-thinking.