| --- |
| license: mit |
| --- |
| # 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 |
