diff --git a/ctlearn/default_models/single_cnn.py b/ctlearn/default_models/single_cnn.py
index 9b3c6f05..e721a752 100644
--- a/ctlearn/default_models/single_cnn.py
+++ b/ctlearn/default_models/single_cnn.py
@@ -49,4 +49,4 @@ def single_cnn_model(data, model_params):
 
         model = tf.keras.Model(network_input, output, name=network_name)
 
-    return model, network_input
+    return model, [network_input]
diff --git a/ctlearn/run_model.py b/ctlearn/run_model.py
index a48c1c90..1209e193 100644
--- a/ctlearn/run_model.py
+++ b/ctlearn/run_model.py
@@ -16,6 +16,7 @@
 
 import tensorflow as tf
 from tensorflow.python import debug as tf_debug
+import tf2onnx
 
 from dl1_data_handler.reader import DL1DataReaderSTAGE1, DL1DataReaderDL1DH
 from ctlearn.data_loader import KerasBatchGenerator
@@ -356,10 +357,14 @@ def run_model(config, mode="train", debug=False, log_to_file=False):
             workers=workers,
             use_multiprocessing=use_multiprocessing,
         )
-
-        model.save(model_dir)
-
         logger.info("Training and evaluating finished succesfully!")
+        model.save(model_dir)
+        logger.info("Keras model saved in {}saved_model.pb".format(model_dir))
+        logger.info("Converting Keras model into ONNX format...")
+        input_type_spec = [input._type_spec for input in backbone_inputs]
+        output_path = model_dir + model.name + ".onnx"
+        tf2onnx.convert.from_keras(model, input_signature=input_type_spec, output_path=output_path)
+        logger.info("ONNX model saved in {}".format(output_path))
 
         # Plotting training history
         training_log = pd.read_csv(model_dir + "/training_log.csv")
diff --git a/environment.yml b/environment.yml
index f99f284b..779aac65 100644
--- a/environment.yml
+++ b/environment.yml
@@ -6,7 +6,7 @@ channels:
     - cta-observatory
     - ctlearn-project
 dependencies:
-    - python=3.10
+    - python=3.9
     - dl1_data_handler=0.10.6
     - astropy
     - matplotlib
@@ -17,5 +17,6 @@ dependencies:
     - scikit-learn
     - pip:
         # TensorFlow via pip
-        - tensorflow
+        - tensorflow==2.8
+        - tf2onnx
         - pydot