Spaces:
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Running
on
T4
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. | |
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## 🔍 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. | |
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## 📊 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% | |