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Add Cloud-Pre Model Card
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Initial commit: Uploaded fine-tuned TimesFM 500M (Cloud-Pre) for Cloud Workloads!
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Verified signature--- license: mit base_model: google/timesfm-2.0-500m-pytorch tags: - time-series-forecasting - timesfm - cloud-computing - resource-forecasting - anomaly-detection datasets: - arashgoshtasbi/cloud-workload-traces metrics: - mae - rmse library_name: timesfm pipeline_tag: time-series-forecasting --- # 🌩️ Cloud-Pre (500M) - Predictive Cloud Auto-scaling Model **Cloud-Pre** is a specialized Time-Series Foundation Model (TSFM) built for the modern cloud era. It is finetuned on top of Google's highly advanced `google/timesfm-2.0-500m-pytorch` framework, explicitly designed to predict and forecast high-frequency cloud infrastructure metrics (CPU, RAM, and Network workloads). ## 🚀 Model Specs - **Architecture:** Decoder-Only Transformer (TimesFM 2.0 Base). - **Parameters:** 500 Million (500M). - **Context Length:** 512 time-steps. - **Horizon Length:** 128 time-steps. - **Developer:** Assem Sabry. ## 🎯 Use Cases This model was trained to help DevOps and Cloud Architects solve the proble…b71e743 -
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