| --- |
| title: Simons Forecast Explorer |
| emoji: 📈 |
| colorFrom: blue |
| colorTo: gray |
| sdk: static |
| app_file: index.html |
| pinned: false |
| license: apache-2.0 |
| short_description: Simons forecasts with and without known-future covariates |
| models: |
| - abel-lab/Simons-25M |
| - abel-lab/Simons-60M |
| - abel-lab/Simons-178M |
| - abel-lab/Simons-297M |
| --- |
| |
| # Simons Forecast Explorer |
|
|
| A forecast explorer for [Simons](https://github.com/Abel-ai-lab/Simons), a family of four small, open time |
| series foundation models for probabilistic forecasting from Abel AI Lab. Pick an example series, a model |
| size, a cutoff and a horizon, and compare the forecast with what happened next. Covariate examples |
| show the forecast with and without known-future covariates in one chart. |
|
|
| Every forecast on the page was computed ahead of time with the `simons` package and the released |
| weights, so the page answers at once: 4 example series, 4 model sizes, 3 horizons and 3 cutoffs |
| each, with and without covariates where the series has them. Model details and weights are on the |
| model cards ([25M](https://huggingface.co/abel-lab/Simons-25M), |
| [60M](https://huggingface.co/abel-lab/Simons-60M), |
| [178M](https://huggingface.co/abel-lab/Simons-178M), |
| [297M](https://huggingface.co/abel-lab/Simons-297M)) and in the |
| [Simons 1 collection](https://huggingface.co/collections/abel-lab/simons-1-6ae3d4ce9705938e293c52dd). |
|
|
| ## How to use it |
|
|
| 1. **Choose a series and a model size:** the 60M model is the default. |
| 2. **Pick the cutoff:** the model reads the history before it (up to 16,384 steps for the 25M and |
| 60M models, 32,768 for the 178M and 297M models). |
| 3. **Pick the horizon:** the number of steps to forecast. |
| 4. **Read the result:** the plot shows the median forecast with its 10-90% and 30-70% bands against |
| the held-out actuals. The table gives the MASE and CRPS of the held-out part for Simons and for a |
| naive forecast (seasonal naive for hourly data, the last value for daily data), lower is better. |
| 5. **Known-future covariates:** where a series has them, the forecasts with and without them are |
| drawn in one chart, with the covariates plotted below. |
|
|
| ## Example data |
|
|
| The ERCOT, Mississippi and Mauna Loa series end in early November 2026. The default forecast of the |
| Mississippi and Mauna Loa series covers their latest values; ERCOT's covers November 5, one full day. The Rossmann series ends in |
| July 2015. ERCOT's covariate is EIA's day-ahead demand forecast: each |
| day's forecast is made the day before, so the model reads it through the end of the day (Central |
| time) on which the forecast starts and forecasts later steps without it. The page stores the plotted |
| part of each series in `data/`. |
|
|
| | Example | Source | Dates | License | |
| |---|---|---|---| |
| | ERCOT electricity demand, hourly, with EIA's day-ahead demand forecast as a known-future covariate | U.S. Energy Information Administration, [Hourly Electric Grid Monitor](https://www.eia.gov/electricity/gridmonitor/) (Form EIA-930), balancing authority ERCO, demand and day-ahead demand forecast in MWh | 2026-08-01 00:00 to 2026-11-07 23:00 UTC | Public domain ([EIA](https://www.eia.gov/about/copyrights_reuse.php)) | |
| | Mississippi River at St. Louis, daily | U.S. Geological Survey, [gauge 07010000](https://waterdata.usgs.gov/monitoring-location/USGS-07010000/), daily mean discharge in ft³/s; recent values are provisional | 2019-01-01 to 2026-11-07 | Public domain ([USGS](https://www.usgs.gov/information-policies-and-instructions/copyrights-and-credits)) | |
| | CO₂ at Mauna Loa, daily | NOAA Global Monitoring Laboratory, [daily mean CO₂ at Mauna Loa](https://gml.noaa.gov/ccgg/trends/data.html) in ppm; days without a measurement are empty, and measurements from December 2022 to July 2023 come from Maunakea | 2016-01-01 to 2026-11-07 | Public domain (U.S. Government work); cite as Dr. Xin Lan, NOAA/GML (gml.noaa.gov/ccgg/trends/) and Dr. Ralph Keeling, Scripps Institution of Oceanography (scrippsco2.ucsd.edu/) | |
| | Rossmann store sales, daily, with promotion days, opening days and school holidays as known-future covariates | [Rossmann Store Sales](https://www.kaggle.com/competitions/rossmann-store-sales) (Kaggle competition), store 1, daily sales; the series comes from [fev-bench](https://huggingface.co/datasets/autogluon/fev_datasets) (`rossmann_1D`) | 2013-01-01 to 2015-07-31 | [Kaggle competition rules](https://www.kaggle.com/competitions/rossmann-store-sales/rules) | |
|
|
| ## Scores |
|
|
| - **MASE:** the mean absolute error of the median forecast, divided by the mean absolute error of a |
| naive forecast over the history: seasonal naive with period 24 (the value a day earlier) for |
| hourly data, and the last value for daily data. |
| - **CRPS:** the mean weighted quantile loss over the 9 quantiles (0.1 to 0.9), divided by the mean |
| absolute actual value. |
|
|
| ## Files |
|
|
| The page is plain HTML, CSS and JavaScript with no build step: `index.html`, `style.css`, `app.js`, |
| the forecasts in `data/` and the logos and fonts in `assets/`. It loads Plotly.js from its CDN. |
| The files in `data/` were computed with the `simons` package and the released weights. |
|
|
| ## License |
|
|
| The code of this Space is licensed under Apache-2.0 and the Simons weights under OpenMDW-1.1. The |
| example data keep the licenses listed above. The Inter font files are under the SIL Open Font |
| License (`assets/fonts/OFL.txt`). |
|
|
