    def forward_on_instance(self, instance: Instance) -> Dict[str, numpy.ndarray]:
        """
        Takes an [`Instance`](../data/instance.md), which typically has raw text in it, converts
        that text into arrays using this model's [`Vocabulary`](../data/vocabulary.md), passes those
        arrays through `self.forward()` and `self.make_output_human_readable()` (which by default
        does nothing) and returns the result.  Before returning the result, we convert any
        `torch.Tensors` into numpy arrays and remove the batch dimension.
        """
        return self.forward_on_instances([instance])[0]
Takes an [`Instance`](../data/instance.md), which typically has raw text in it, converts
that text into arrays using this model's [`Vocabulary`](../data/vocabulary.md), passes those
arrays through `self.forward()` and `self.make_output_human_readable()` (which by default
does nothing) and returns the result.  Before returning the result, we convert any
`torch.Tensors` into numpy arrays and remove the batch dimension.
allennlp/models/model.py