timesfm-forecasting
Zero-shot time series forecasting with Google's TimesFM foundation model. Use for any univariate time series (sales, sensors, energy, vitals, weather) without training a custom model. Supports CSV/DataFrame/array inputs with point forecasts and prediction intervals. Includes a preflight system checker script to verify RAM/GPU before first use.
Details
- Path
- skills/timesfm-forecasting
- License
- Apache-2.0 license
- Allowed tools
- 1
- Bundled scripts
- 10
- Dependencies
- 2
Allowed tools
Read Write Edit Bash
Bundled scripts
- skills/timesfm-forecasting/examples/covariates-forecasting/demo_covariates.py
- skills/timesfm-forecasting/examples/anomaly-detection/detect_anomalies.py
- skills/timesfm-forecasting/examples/global-temperature/run_example.sh
- skills/timesfm-forecasting/examples/global-temperature/run_forecast.py
- skills/timesfm-forecasting/examples/global-temperature/generate_html.py
- skills/timesfm-forecasting/examples/global-temperature/visualize_forecast.py
- skills/timesfm-forecasting/examples/global-temperature/generate_animation_data.py
- skills/timesfm-forecasting/examples/global-temperature/generate_gif.py
- skills/timesfm-forecasting/scripts/forecast_csv.py
- skills/timesfm-forecasting/scripts/check_system.py