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Forecaster

MomentFMForecaster

API referenceSource
Categorical in XMultivariate

Interface for forecasting with the deep learning time series model momentfm.

Quickstart

python
from sktime.forecasting.momentfm import MomentFMForecaster

estimator = MomentFMForecaster(pretrained_model_name_or_path='AutonLab/MOMENT-1-large', freeze_encoder=True, freeze_embedder=True, freeze_head=False, dropout=0.1, head_dropout=0.1, seq_len=512, batch_size=32, eval_batch_size=32, epochs=1, max_lr=0.0001, device='auto', pct_start=0.3, max_norm=5.0, train_val_split=0.2, transformer_backbone='google/flan-t5-large', criterion=None, config=None, return_model_to_cpu=False)

Examples

>>> from sktime.forecasting.momentfm import MomentFMForecaster
>>> from sktime.datasets import load_airline
>>> y = load_airline ()
>>> forecaster = MomentFMForecaster (seq_len = 2)
>>> forecaster. fit (y, fh = [1, 2, 3 ])
>>> y_pred = forecaster. predict (y = y)

References

  1. Paper: https://arxiv.org/abs/2402.03885 Github: https://github.com/moment-timeseries-foundation-model/moment/tree/main