text: Title: [DOC] How does one initialise a network without `from_dataset`?
  Body: ### Expected behavior
  Code:
  
  ```
  from pytorch_forecasting.models import NBeats, BaseModel
  from pytorch_lightning import Trainer, LightningModule
  
  model = NBeats()
  trainer.fit(model, train, valid)
  
  ```
  Result:
  
  ```
  ---------------------------------------------------------------------------
  TypeError                                 Traceback (most recent call last)
  [<ipython-input-102-a9a3146dfc98>](https://localhost:8080/#) in <cell line: 1>()
  ----> 1 trainer.fit(model, train,valid)
  
  1 frames
  [/usr/local/lib/python3.10/dist-packages/pytorch_lightning/utilities/compile.py](https://localhost:8080/#) in _maybe_unwrap_optimized(model)
      130         return model
      131     _check_mixed_imports(model)
  --> 132     raise TypeError(
      133         f"`model` must be a `LightningModule` or `torch._dynamo.OptimizedModule`, got `{type(model).__qualname__}`"
      134     )
  
  TypeError: `model` must be a `LightningModule` or `torch._dynamo.OptimizedModule`, got `NBeats`
  ```
  
  I'm trying to use the naked networks without the rest of the stuff around pytorch_forecasting. 
  
  I've read the source code I do believe this should work; but I must be doing something stupid.
  
  Is it possible to add an example or FAQ of how to use pytorch_forecasting without `from_dataset`?