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PredictiX Asset Summary Generation Model

🧾 Overview

The PredictiX Asset Summary Generation Model is designed to generate concise and informative summaries of asset conditions in a fleet or warehouse management system. It helps decision-makers quickly understand asset health, maintenance needs, and operational risks.

🎯 Task

Task Type: Text Summarization
Domain: Fleet Management / Warehouse Monitoring
Objective: Generate high-level summaries from structured and unstructured asset data

📊 Dataset

Total Records: 3,000+
Features: 70+ columns
Data Includes:
- Asset/vehicle information
- Sensor readings (temperature, vibration, etc.)
- Maintenance history
- Operational status
- Failure predictions

🧠 Model Details

Base Model: (Fill this – e.g., facebook/bart-base or t5-small)
Fine-tuned for: Asset Summary Generation
Framework: Hugging Face Transformers
Language: English

⚙️ Input Format

The model expects structured or semi-structured asset data converted into text format.

Example Input

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Safetensors

Model size

0.4B params

Tensor type

F32

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Dinusha-Ekanayake
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predictix-asset_summarization_model