Nixtla's Open Source Time Series Ecosystem.

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Hi <@U06204WKHPC>! `batch_size` corresponds to the number of time series in the batch, and `windows_batch_size` to the number of windows in the batch. During each training iteration, the loader first sample `batch_size` series, then the model selects `windows_batch_size` windows at random starting at different timestamps.

Thanks for the suggestion on the `predict` method, this was requested by several users already. We will add this functionality soon :slightly_smiling_face:

Thank you very much Cristian!, Also, a quick question, suppose I want to implement some other models (such as TiDE) with neuralforecast framework. What I need to to is to write the 'Model' and 'AutoModel' inherit from the exisitng 'BaseWindow' and 'BaseAuto'. then theoretically it should work?

Hey. We have a <https://nixtla.github.io/neuralforecast/examples/how_to_add_models.html|guide> for this. Please let us know if something is missing from it

And also this one can be useful: <https://nixtla.github.io/neuralforecast/examples/neuralforecast_map.html>

It would be awesome if you can add it to the library. If you set a PR we can help you!