| tags: | |
| - time-series-forecasting | |
| - cloud-computing | |
| - timesfm | |
| - resource-prediction | |
| # 🌩️ Cloud-Pre (500M) | |
| **Cloud-Pre** is a specialized time-series foundation model designed for predicting cloud environment resource usage (CPU, RAM, Network). | |
| It is fine-tuned based on Google's highly advanced `google/timesfm-2.0-500m-pytorch`. | |
| ## Model Details | |
| - **Architecture:** Decoder-Only Transformer (TimesFM 2.0 Base) | |
| - **Parameters:** 500 Million | |
| - **Fine-tuning Objective:** Cloud CPU/Resource peak and anomaly forecasting to aid with Predictive Auto-scaling. | |
| - **Developer:** Assem Sabry | |
| ## How to find the training code? | |
| The complete open-source training pipeline and data engineering scripts can be found on my GitHub Repository. |