diff --git a/src/eynollah/cli/cli_readingorder.py b/src/eynollah/cli/cli_readingorder.py
index 0f44b7f..eed9fb9 100644
--- a/src/eynollah/cli/cli_readingorder.py
+++ b/src/eynollah/cli/cli_readingorder.py
@@ -20,14 +20,19 @@ import click
     type=click.Path(exists=True, file_okay=False),
     required=True,
 )
+@click.option(
+    "--device",
+    "-D",
+    help="placement of computations in predictors for each model type; if none (by default), will try to use first available GPU or fall back to CPU; set string to force using a device (e.g. 'GPU0', 'GPU1' or 'CPU'). Can also be a comma-separated list of model category to device mappings (e.g. 'col_classifier:CPU,page:GPU0,*:GPU1')",
+)
 @click.pass_context
-def readingorder_cli(ctx, input, dir_in, out):
+def readingorder_cli(ctx, input, dir_in, out, device):
     """
     Generate ReadingOrder with a ML model
     """
-    from ..mb_ro_on_layout import machine_based_reading_order_on_layout
+    from ..mb_ro_on_layout import Reorder
     assert bool(input) != bool(dir_in), "Either -i (single input) or -di (directory) must be provided, but not both."
-    orderer = machine_based_reading_order_on_layout(model_zoo=ctx.obj.model_zoo)
+    orderer = Reorder(model_zoo=ctx.obj.model_zoo, device=device)
     orderer.run(xml_filename=input,
                 dir_in=dir_in,
                 dir_out=out,
diff --git a/src/eynollah/mb_ro_on_layout.py b/src/eynollah/mb_ro_on_layout.py
index 22fe97b..5725ba1 100644
--- a/src/eynollah/mb_ro_on_layout.py
+++ b/src/eynollah/mb_ro_on_layout.py
@@ -21,6 +21,7 @@ os.environ['TF_USE_LEGACY_KERAS'] = '1' # avoid Keras 3 after TF 2.15
 import tensorflow as tf
 from tensorflow.keras.models import Model
 
+from .eynollah import Eynollah
 from .model_zoo import EynollahModelZoo
 from .utils.resize import resize_image
 from .utils.contour import (
@@ -34,23 +35,27 @@ DPI_THRESHOLD = 298
 KERNEL = np.ones((5, 5), np.uint8)
 
 
-class machine_based_reading_order_on_layout:
+class Reorder(Eynollah):
     def __init__(
-        self,
-        *,
-        model_zoo: EynollahModelZoo,
-        logger : Optional[logging.Logger] = None,
+            self,
+            *,
+            model_zoo: EynollahModelZoo,
+            logger : Optional[logging.Logger] = None,
+            device: str = '',
     ):
         self.logger = logger or logging.getLogger('eynollah.mbreorder')
         self.model_zoo = model_zoo
         
-        try:
-            for device in tf.config.list_physical_devices('GPU'):
-                tf.config.experimental.set_memory_growth(device, True)
-        except:
-            self.logger.warning("no GPU device available")
-            
         self.model_zoo.load_model('reading_order')
+        self.setup_models(device=device)
+
+    def setup_models(self, device=''):
+        loadable = ['reading_order']
+        self.model_zoo.load_models(*loadable, device=device)
+        for model in loadable:
+            self.logger.debug("model %s has input shape %s", model,
+                              self.model_zoo.get(model).input_shape)
+        
 
     def read_xml(self, xml_file):
         tree1 = ET.parse(xml_file, parser = ET.XMLParser(encoding='utf-8'))
@@ -676,7 +681,7 @@ class machine_based_reading_order_on_layout:
                 tot_counter += 1
                 batch.append(j)
                 if tot_counter % inference_bs == 0 or tot_counter == len(ij_list):
-                    y_pr = self.model_zoo.get('reading_order', Model).predict(input_1 , verbose='0')
+                    y_pr = self.model_zoo.get('reading_order').predict(input_1, verbose=0)
                     for jb, j in enumerate(batch):
                         if y_pr[jb][0]>=0.5:
                             post_list.append(j)