diff --git a/mhcflurry/batch_generator.py b/mhcflurry/batch_generator.py
index 570cc8adcf430892e305d726bad8691ec0e8f9e9..ca51207201b98d83040a1ecefe37e35c23310666 100644
--- a/mhcflurry/batch_generator.py
+++ b/mhcflurry/batch_generator.py
@@ -103,7 +103,7 @@ class MultiallelicMassSpecBatchGenerator(object):
         batch_generator_batch_size=128,
         batch_generator_affinity_fraction=0.5)
     """
-    Hyperperameters for batch generation for the ligandome predictor.
+    Hyperperameters for batch generation for the presentation predictor.
     """
 
     def __init__(self, hyperparameters):
diff --git a/mhcflurry/class1_presentation_neural_network.py b/mhcflurry/class1_presentation_neural_network.py
index db3a25350476eabf937b8b29cceaeb6a65e188fa..897fafd854d437a269a83c59fb30cca2469dc9a7 100644
--- a/mhcflurry/class1_presentation_neural_network.py
+++ b/mhcflurry/class1_presentation_neural_network.py
@@ -195,22 +195,23 @@ class Class1PresentationNeuralNetwork(object):
                 [node, auxiliary_input], name="affinities_with_auxiliary")
 
         layer = Dense(8, activation="tanh")
-        lifted = TimeDistributed(layer, name="ligandome_hidden1")
+        lifted = TimeDistributed(layer, name="presentation_hidden1")
         node = lifted(node)
 
         layer = Dense(1, activation="tanh")
-        lifted = TimeDistributed(layer, name="ligandome_output")
-        ligandome_adjustment = lifted(node)
+        lifted = TimeDistributed(layer, name="presentation_hidden2")
+        presentation_adjustment = lifted(node)
 
         def logit(x):
             import tensorflow as tf
             return - tf.log(1. / x - 1.)
 
-        ligandome_output_pre_sigmoid = Add()([
+        presentation_output_pre_sigmoid = Add()([
             Lambda(logit)(affinity_predictor_matrix_output),
-            ligandome_adjustment,
+            presentation_adjustment,
         ])
-        ligandome_output = Activation("sigmoid")(ligandome_output_pre_sigmoid)
+        presentation_output = Activation("sigmoid", name="presentation_output")(
+            presentation_output_pre_sigmoid)
 
         self.network = Model(
             inputs=[
@@ -219,10 +220,10 @@ class Class1PresentationNeuralNetwork(object):
             ] + ([] if auxiliary_input is None else [auxiliary_input]),
             outputs=[
                 affinity_predictor_output,
-                ligandome_output,
+                presentation_output,
                 affinity_predictor_matrix_output
             ],
-            name="ligandome",
+            name="presentation",
         )
         self.network.summary()
 
diff --git a/mhcflurry/class1_presentation_predictor.py b/mhcflurry/class1_presentation_predictor.py
index 1471ad974dba121e5a6b07264c99f33febf32fcf..625b32f4fd7c70e8164b7ce4a026819e51569166 100644
--- a/mhcflurry/class1_presentation_predictor.py
+++ b/mhcflurry/class1_presentation_predictor.py
@@ -36,11 +36,11 @@ from .custom_loss import (
 class Class1PresentationPredictor(object):
     def __init__(
             self,
-            class1_ligandome_neural_networks,
+            class1_presentation_neural_networks,
             allele_to_sequence,
             manifest_df=None,
             metadata_dataframes=None):
-        self.networks = class1_ligandome_neural_networks
+        self.networks = class1_presentation_neural_networks
         self.allele_to_sequence = allele_to_sequence
         self._manifest_df = manifest_df
         self.metadata_dataframes = (
diff --git a/mhcflurry/multiallelic_refinement_command.py b/mhcflurry/multiallelic_refinement_command.py
index 1e47e77f5d7c6e0bbd40df8f56d3951d5833fa69..324efff0b16641ffc12e4e74d97cd05ee9f32748 100644
--- a/mhcflurry/multiallelic_refinement_command.py
+++ b/mhcflurry/multiallelic_refinement_command.py
@@ -57,17 +57,17 @@ parser.add_argument(
 parser.add_argument(
     "--hyperparameters",
     metavar="FILE.json",
-    help="Ligandome predictor hyperparameters")
+    help="presentation predictor hyperparameters")
 parser.add_argument(
     "--out-affinity-predictor-dir",
     metavar="DIR",
     required=True,
     help="Directory to write refined models")
 parser.add_argument(
-    "--out-ligandome-predictor-dir",
+    "--out-presentation-predictor-dir",
     metavar="DIR",
     required=True,
-    help="Directory to write ligandome predictors")
+    help="Directory to write preentation predictor")
 parser.add_argument(
     "--verbosity",
     type=int,
@@ -89,8 +89,8 @@ def run(argv=sys.argv[1:]):
 
     args.out_affinity_predictor_dir = os.path.abspath(
         args.out_affinity_predictor_dir)
-    args.out_ligandome_predictor_dir = os.path.abspath(
-        args.out_ligandome_predictor_dir)
+    args.out_presentation_predictor_dir = os.path.abspath(
+        args.out_presentation_predictor_dir)
 
     configure_logging(verbose=args.verbosity > 1)
 
diff --git a/test/test_class1_presentation_predictor.py b/test/test_class1_presentation_predictor.py
index 768d270a42df15df2fbdfa0341b5eb6b14951a03..bbd0bf1e4385d53fed16a73b88d402945271c946 100644
--- a/test/test_class1_presentation_predictor.py
+++ b/test/test_class1_presentation_predictor.py
@@ -56,7 +56,6 @@ def data_path(name):
     return os.path.join(os.path.dirname(__file__), "data", name)
 
 
-
 def setup():
     global PAN_ALLELE_PREDICTOR_NO_MASS_SPEC
     global PAN_ALLELE_MOTIFS_WITH_MASS_SPEC_DF