Fraud · Safety JSONL

INDIA_FRAUD_DETECTION_JSONL_V1

100 synthetic fraud & scam scenarios · CC-BY-4.0

Legal JSONL

LEGAL_ASSISTANT_DATASET_JSONL_INDIA

60 synthetic legal & crime-safety scenarios · CC-BY-4.0

Wellbeing JSONL

VNOVA_AI_EMOTIONAL_SUPPORT_DATASET_V1

100 synthetic emotional support scenarios · CC-BY-4.0

Cybersecurity JSONL

CYBERSECURITY_JSONL_V1

100 synthetic cybersecurity scenarios · CC-BY-4.0

Reasoning JSONL

DECISION_MAKING_ASSISTANT_DATASET_V1_JSONL

100 synthetic decision-making scenarios · CC-BY-4.0

Customer Support JSONL

CUSTOMER_SUPPORT_DATASET_JSONL_V1

100 synthetic customer support scenarios · CC-BY-4.0

Emergency JSONL

EMERGENCY_DISASTER_RESPONSE_V1_JSONL

100 synthetic emergency & disaster response scenarios · CC-BY-4.0

Business JSONL

STARTUP_STRATEGY_DATASET_JSONL_V1

100 synthetic startup strategy scenarios · CC-BY-4.0

Code · Tutor JSONL

VNOVA_AI_CODING_LOGIC_TUTOR_DATASET_V1_JSONL

100 synthetic coding logic scenarios · CC-BY-4.0

Creativity JSONL

AI_Creativity_Booster_Dataset_V1_JSONL

100 synthetic AI creativity-booster scenarios · CC-BY-4.0

Industry JSONL

Emerging_AI-First_Industries_V1_JSONL

100 synthetic emerging AI-first industry scenarios · CC-BY-4.0

Agents JSONL

ai_agent_and_automation_dataset_v1_jsonl

100 synthetic AI agent & automation scenarios · CC-BY-4.0

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Quickstart

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All VNOVA AI datasets follow standard Hugging Face schemas. Install the datasets library and load by name.

Browse all on Hugging Face
python
# Python — using the Hugging Face datasets library
from datasets import load_dataset

ds = load_dataset("vnovaai/INDIA_FRAUD_DETECTION_JSONL_V1")
print(ds["train"][0])

# JSONL fields: instruction / input / output