# neural-forecast

Guillaume GALIE

09/21/2023, 1:21 PM
Hello Sorry in advance if my questions are really basic for some of you : 1/ while using a pretrained model (transfer learning), I am not able to pass horizon h with predicton function, why ? use case : how can I produce a prediction for next 36 months if the trained models was trained on 24 past months ? 2/ may I finetune a model with exogenous variables while the trained model was not trained with exogenous variables ? Thank you

Cristian (Nixtla)

09/21/2023, 4:06 PM
Hi @Guillaume GALIE! The architecture of all the models in the library (expect DeepAR) depends on the horizon because they follow the "direct" forecasting strategy. When a model is trained with a particular horizon, it can't be changed afterwards.
There are two options: 1. Train the model on the longest horizon of interest, and simply trim the extra information. 2. Implement a recursive predict method, where you use the forecast as input for the next window.
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Is the same issue with the exogenous variables