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Hello @virgilio espina! Thanks for the interest in our library. These models are univariate, meaning that they produce forecasts for each time-series independently from the rest. However, these are "global models", so the same model is trained and used to forecast all the time-series of your dataset. Our research (and many other papers) show that these global univariate models forecast more accurately than the most recent multivariate models. Here is a link to the most recent documentation on how to use them: https://nixtla.github.io/neuralforecast/examples/getting_started_with_nbeats_and_nhits.html

Hello @Cristian (Nixtla). thank you for the response. The link says "File not found".

Hi! Here is the link of the updated version: https://nixtla.github.io/neuralforecast/examples/getting_started.html

thank you for this link. now I know that this models are momentarily for univariate forecasting. please let me know if the system have added for multivariate models. thanks.