diff --git a/gunpowder/torch/nodes/predict.py b/gunpowder/torch/nodes/predict.py
index 89c9ac0c..3bc58344 100644
--- a/gunpowder/torch/nodes/predict.py
+++ b/gunpowder/torch/nodes/predict.py
@@ -18,10 +18,10 @@ class Predict(GenericPredict):
 
             The model to use for prediction.
 
-        inputs (``dict``, ``string`` -> :class:`ArrayKey`):
+        inputs (``dict``, ``string`` or ``int`` -> :class:`ArrayKey`):
 
-            Dictionary from the names of input tensors (argument names of the
-            ``forward`` method) in the model to array keys.
+            Dictionary from the position (for args) and names (for kwargs) of input
+            tensors (argument names of the ``forward`` method) in the model to array keys.
 
         outputs (``dict``, ``string`` or ``int`` -> :class:`ArrayKey`):
 
@@ -58,7 +58,7 @@ class Predict(GenericPredict):
     def __init__(
         self,
         model,
-        inputs: Dict[str, ArrayKey],
+        inputs: Dict[Union[str, int], ArrayKey],
         outputs: Dict[Union[str, int], ArrayKey],
         array_specs: Optional[Dict[ArrayKey, ArraySpec]] = None,
         checkpoint: Optional[str] = None,
@@ -111,18 +111,24 @@ def start(self):
         self.register_hooks()
 
     def predict(self, batch, request):
-        inputs = self.get_inputs(batch)
+        input_args, input_kwargs = self.get_inputs(batch)
         with torch.no_grad():
-            out = self.model.forward(**inputs)
+            out = self.model.forward(*input_args, **input_kwargs)
         outputs = self.get_outputs(out, request)
         self.update_batch(batch, request, outputs)
 
     def get_inputs(self, batch):
-        model_inputs = {
+        model_args = [
+            torch.as_tensor(batch[self.inputs[ii]].data, device=self.device)
+            for ii in range(len(self.inputs))
+            if ii in self.inputs
+        ]
+        model_kwargs = {
             key: torch.as_tensor(batch[value].data, device=self.device)
             for key, value in self.inputs.items()
+            if isinstance(key, str)
         }
-        return model_inputs
+        return model_args, model_kwargs
 
     def register_hooks(self):
         for key in self.outputs: