def load_weights(
        self, path: str, load_encoders: bool = True, skip_checks: bool = False, **kwargs
    ):
        """
        Loads the weights from a manually saved model (saved with :meth:`save() <TorchForecastingModel.save()>`).

        Note: This method needs to be able to access the darts model checkpoint (.pt) in order to load the encoders
        and perform sanity checks on the model parameters.

        Parameters
        ----------
        path
            Path from which to load the model's weights. If no path was specified when saving the model, the
            automatically generated path ending with ".pt" has to be provided.
        load_encoders
            If set, will load the encoders from the model to enable direct call of fit() or predict().
            Default: ``True``.
        skip_checks
            If set, will disable the loading of the encoders and the sanity checks on model parameters
            (not recommended). Cannot be used with `load_encoders=True`. Default: ``False``.
        **kwargs
            Additional kwargs for PyTorch's :func:`load` method, such as ``map_location`` to load the model onto a
            different device than the one from which it was saved.
            For more information, read the `official documentation <https://pytorch.org/docs/stable/generated/
            torch.load.html>`_.

        """
        path_ptl_ckpt = path + ".ckpt"
        raise_if_not(
            os.path.exists(path_ptl_ckpt),
            f"Could not find PyTorch LightningModule checkpoint {path_ptl_ckpt}.",
            logger,
        )

        self.load_weights_from_checkpoint(
            file_name=path_ptl_ckpt,
            load_encoders=load_encoders,
            skip_checks=skip_checks,
            **kwargs,
        )

        Loads the weights from a manually saved model (saved with :meth:`save() <TorchForecastingModel.save()>`).

        Note: This method needs to be able to access the darts model checkpoint (.pt) in order to load the encoders
        and perform sanity checks on the model parameters.

        Parameters
        ----------
        path
            Path from which to load the model's weights. If no path was specified when saving the model, the
            automatically generated path ending with ".pt" has to be provided.
        load_encoders
            If set, will load the encoders from the model to enable direct call of fit() or predict().
            Default: ``True``.
        skip_checks
            If set, will disable the loading of the encoders and the sanity checks on model parameters
            (not recommended). Cannot be used with `load_encoders=True`. Default: ``False``.
        **kwargs
            Additional kwargs for PyTorch's :func:`load` method, such as ``map_location`` to load the model onto a
            different device than the one from which it was saved.
            For more information, read the `official documentation <https://pytorch.org/docs/stable/generated/
            torch.load.html>`_.

        
darts/models/forecasting/torch_forecasting_model.py