Granite Timeseries Patchtsmixer
A time series forecasting model based on the PatchTSMixer architecture, developed by IBM, suitable for multivariate time series forecasting tasks.
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Release Time : 11/22/2024
Model Overview
This model is specifically designed for time series forecasting, utilizing the PatchTSMixer architecture to handle multivariate time series data, applicable to various prediction scenarios.
Model Features
Multivariate Time Series Processing
Capable of handling multiple time series variables simultaneously, suitable for complex forecasting scenarios.
ONNX Format Compatibility
The model has been converted to ONNX format, facilitating deployment and usage in web environments.
Transformers.js Integration
Optimized for Transformers.js, allowing direct usage in JavaScript environments.
Model Capabilities
Multivariate Time Series Forecasting
Long-term Time Series Modeling
Time Series Pattern Recognition
Use Cases
Business Forecasting
Sales Forecasting
Predict future sales trends over a specified period.
Inventory Demand Forecasting
Predict future inventory needs to optimize supply chain management.
Financial Analysis
Stock Price Prediction
Forecast future trends in financial time series.
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