Datasets:
metadata
license: cc-by-nc-4.0
language:
- en
task_categories:
- text2text-generation
tags:
- vehicle-diagnostics
- automotive
- telemetry
- predictive-maintenance
- industrial-ai
pretty_name: Vehicle Diagnostic Sample Dataset
size_categories:
- n<100
Vehicle Diagnostic Sample Dataset
🧩 Dataset Summary
This dataset contains a sample subset of structured vehicle diagnostic logs generated for various vehicle types and subsystems, such as transmissions, battery systems, brakes, and engines. Each entry includes detailed parameters such as fault codes, performance metrics, measurements, temporal trends, and maintenance recommendations.
This subset (500 examples) is meant to demonstrate the structure and potential use cases of the full dataset available commercially on Gumroad for industrial, machine learning, and predictive maintenance applications.
💡 Use Cases
- Train models for fault prediction and diagnosis generation
- Fine-tune text-to-text models on structured industrial reports
- Build synthetic data generators for simulation platforms
- Analyze parameter trends for telemetry-driven maintenance planning
📁 Dataset Structure
Each entry follows the structure:
{
"input": "Generate comprehensive vehicle diagnostic for <vehicle> <system> system, config=<config>",
"output": "<structured diagnostic report with parameters, metrics, fault code, and recommendations>"
}
🧪 Example
{
"input": "Generate comprehensive vehicle diagnostic for commercial transmission system, config=automatic",
"output": "Diagnostic ID=17f869b8... torque=261.78 Nm... Maintenance Recommendations: filter replacement, fluid change, seal inspection"
}
📥 Loading the Dataset in Python
from datasets import load_dataset
dataset = load_dataset("cjjones/vehicle-diagnostic-sample")
print(dataset["train"][0])