Chronos2Forecaster

Interface to the Chronos-2 Zero-Shot Forecaster by Amazon Research.

Quickstart

from sktime.forecasting.chronos2 import Chronos2Forecaster

estimator = Chronos2Forecaster(model_path: str='amazon/chronos-2', config: dict=None, seed: int | None=None, ignore_deps: bool=False)

Parameters(4)

model_pathstr, default=”amazon/chronos-2”

Path to the Chronos-2 HuggingFace model.

configdict, optional, default=None

Configuration overrides. Supported keys:

• “limit_prediction_length”bool, default=False

  If True, raises an error when prediction_length exceeds the model’s maximum prediction length.

seedint or None, optional, default=None

Random seed for reproducibility.

ignore_depsbool, optional, default=False

If True, dependency checks are skipped.

Examples

>>> from sktime.datasets import load_airline
>>> from sktime.forecasting.chronos2 import Chronos2Forecaster
>>> from sktime.split import temporal_train_test_split
>>> y = load_airline ()
>>> y_train, y_test = temporal_train_test_split (y)
>>> forecaster = Chronos2Forecaster ("amazon/chronos-2")
>>> forecaster. fit (y_train)
>>> y_pred = forecaster. predict (fh = [1, 2, 3 ])

References

1. [1 ] https://github.com/amazon-science/chronos-forecasting [2 ] (1, 2) Abdul Fatir Ansari and others (2025). Chronos-2: Towards a Universal, General-Purpose Forecasting Foundation Model.