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| title: Test | |
| emoji: 🦖 | |
| colorFrom: green | |
| colorTo: blue | |
| sdk: docker | |
| app_port: 7860 | |
| # TiRex – Zero‑Shot Time Series Forecasting App | |
| A Gradio‑based interactive web app to perform zero‑shot time series forecasting using the TiRex model. Upload your own CSV/XLSX/Parquet files or choose from built‑in presets, filter series by name, and visualize quantile forecasts over your chosen horizon. | |
| --- | |
| ## 🔍 Features | |
| - **Zero‑Shot Forecasting**: Powered by the [`NX-AI/TiRex`](https://huggingface.co/NX-AI/TiRex) model. | |
| - **Custom Data Upload**: Accepts CSV, XLSX, and Parquet. | |
| - **Preset Datasets**: Includes `loop.csv`, `air_passangers.csv`, and `ett2.csv` for quick demos. | |
| - **Interactive Filtering**: Search, check/uncheck, and plot only the series you care about. | |
| - **Quantile Forecasts**: Displays historical data, median forecast line, and 10–90% quantile shading. | |
| - **Configurable Horizon**: Slider to set forecast length (1–512 steps). | |
| - **Automatic Defaults**: Detects best forecast‐length defaults for presets. | |
| --- | |
| ## 📊 Data Format | |
| ### With Named Series | |
| ```csv | |
| AAPL,120.5,121.0,119.8,122.1,123.5,... | |
| AMZN,3300.0,3310.5,3295.2,3305.8,3315.1,... | |
| GOOGL,2800.1,2795.3,2810.7,2805.2,2820.4,... | |
| ``` | |
| ### Without Named Series | |
| ```csv | |
| 120.5,121.0,119.8,122.1,123.5,... | |
| 3300.0,3310.5,3295.2,3305.8,3315.1,... | |
| 2800.1,2795.3,2810.7,2805.2,2820.4,... | |
| ``` | |
| ### Key Rules: | |
| - **One row per time series** | |
| - **Consistent naming**: Either all rows have names (first column) or none do | |
| - **Numeric data**: All values after the optional name column must be numeric | |
| - **Minimum length**: Time series must have at least `forecast_length + 10` data points | |
| - **Maximum constraints**: Up to 30 time series and 2048 time steps per series | |
| ## 🔧 Configuration | |
| ### Forecast Length | |
| - **Default**: 64 steps | |
| - **Range**: 1-512 steps | |
| - **Auto-adjustment**: Preset datasets have optimized forecast lengths: | |
| - `loop.csv` and `ett2.csv`: 256 steps | |
| - `air_passangers.csv`: 48 steps | |
| ### Model Settings | |
| - **Device**: CUDA (T4 GPU) | |
| - **Quantiles**: 10%, 50% (median), 90% prediction intervals | |
| ## 📈 Output Features | |
| - **Historical data**: Blue line showing input time series | |
| - **Median forecast**: Orange line for point predictions | |
| - **Uncertainty bands**: Gray shaded area showing 10%-90% | |