diff --git a/gunpowder/torch/nodes/predict.py b/gunpowder/torch/nodes/predict.py
index 585ebc34..89c9ac0c 100644
--- a/gunpowder/torch/nodes/predict.py
+++ b/gunpowder/torch/nodes/predict.py
@@ -85,10 +85,13 @@ def __init__(
         self.intermediate_layers: dict[ArrayKey, Any] = {}
 
     def start(self):
-        self.use_cuda = torch.cuda.is_available() and self.device_string == "cuda"
-        logger.info(f"Predicting on {'gpu' if self.use_cuda else 'cpu'}")
-        self.device = torch.device("cuda" if self.use_cuda else "cpu")
+        # Issue #188
+        self.use_cuda = torch.cuda.is_available() and self.device_string.__contains__(
+            "cuda"
+        )
 
+        logger.info(f"Predicting on {'gpu' if self.use_cuda else 'cpu'}")
+        self.device = torch.device(self.device_string if self.use_cuda else "cpu")
         try:
             self.model = self.model.to(self.device)
         except RuntimeError as e:
diff --git a/gunpowder/torch/nodes/train.py b/gunpowder/torch/nodes/train.py
index 3f688929..e913d8ad 100644
--- a/gunpowder/torch/nodes/train.py
+++ b/gunpowder/torch/nodes/train.py
@@ -79,6 +79,12 @@ class Train(GenericTrain):
         spawn_subprocess (``bool``, optional):
 
             Whether to run the ``train_step`` in a separate process. Default is false.
+
+        device (``str``, optional):
+
+            Accepts a cuda gpu specifically to train on (e.g. `cuda:1`, `cuda:2`), helps in multi-card systems.
+            defaults to ``cuda``
+
     """
 
     def __init__(
@@ -93,9 +99,10 @@ def __init__(
         array_specs: Optional[Dict[ArrayKey, ArraySpec]] = None,
         checkpoint_basename: str = "model",
         save_every: int = 2000,
-        log_dir: Optional[str] = None,
+        log_dir: str = None,
         log_every: int = 1,
         spawn_subprocess: bool = False,
+        device: str = "cuda",
     ):
         if not model.training:
             logger.warning(
@@ -125,6 +132,7 @@ def __init__(
         self.loss_inputs = loss_inputs
         self.checkpoint_basename = checkpoint_basename
         self.save_every = save_every
+        self.dev = device
 
         self.iteration = 0
 
@@ -167,7 +175,8 @@ def retain_gradients(self, request, outputs):
 
     def start(self):
         self.use_cuda = torch.cuda.is_available()
-        self.device = torch.device("cuda" if self.use_cuda else "cpu")
+        # Issue: #188
+        self.device = torch.device(self.dev if self.use_cuda else "cpu")
 
         try:
             self.model = self.model.to(self.device)