diff --git a/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/fingerprint.pb b/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/fingerprint.pb
new file mode 100644
index 00000000..f6ea8da2
--- /dev/null
+++ b/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/fingerprint.pb
@@ -0,0 +1 @@
+Ðæ²¦É„ý‡%æÌŸë•�Í‰ä ¥• äçðäµ âìÎ£¤âÌÏò(öÐ‹ÎÜ‡üÂ}2
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diff --git a/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/keras_metadata.pb b/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/keras_metadata.pb
new file mode 100644
index 00000000..5fe8f1a6
--- /dev/null
+++ b/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/keras_metadata.pb
@@ -0,0 +1,7 @@
+
+Õ&root"_tf_keras_sequential*°&{"name": "sequential", "trainable": true, "expects_training_arg": true, "dtype": "float32", "batch_input_shape": null, "must_restore_from_config": false, "preserve_input_structure_in_config": false, "autocast": false, "class_name": "Sequential", "config": {"name": "sequential", "layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": {"class_name": "__tuple__", "items": [null, 5, 3]}, "dtype": "float32", "sparse": false, "ragged": false, "name": "input_1"}}, {"class_name": "LSTM", "config": {"name": "lstm", "trainable": true, "dtype": "float32", "return_sequences": false, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 32, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 1}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}, "shared_object_id": 2}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 3}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}}, {"class_name": "Dense", "config": {"name": "dense", "trainable": true, "dtype": "float32", "units": 1, "activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}}, "bias_initializer": {"class_name": "Zeros", "config": {}}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}}]}, "shared_object_id": 9, "input_spec": [{"class_name": "InputSpec", "config": {"dtype": null, "shape": {"class_name": "__tuple__", "items": [null, 5, 3]}, "ndim": 3, "max_ndim": null, "min_ndim": null, "axes": {}}}], "build_input_shape": {"class_name": "TensorShape", "items": [null, 5, 3]}, "is_graph_network": true, "full_save_spec": {"class_name": "__tuple__", "items": [[{"class_name": "TypeSpec", "type_spec": "tf.TensorSpec", "serialized": [{"class_name": "TensorShape", "items": [null, 5, 3]}, "float32", "input_1"]}], {}]}, "save_spec": {"class_name": "TypeSpec", "type_spec": "tf.TensorSpec", "serialized": [{"class_name": "TensorShape", "items": [null, 5, 3]}, "float32", "input_1"]}, "keras_version": "2.12.0", "backend": "tensorflow", "model_config": {"class_name": "Sequential", "config": {"name": "sequential", "layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": {"class_name": "__tuple__", "items": [null, 5, 3]}, "dtype": "float32", "sparse": false, "ragged": false, "name": "input_1"}, "shared_object_id": 0}, {"class_name": "LSTM", "config": {"name": "lstm", "trainable": true, "dtype": "float32", "return_sequences": false, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 32, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 1}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}, "shared_object_id": 2}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 3}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}, "shared_object_id": 5}, {"class_name": "Dense", "config": {"name": "dense", "trainable": true, "dtype": "float32", "units": 1, "activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 6}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 7}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}, "shared_object_id": 8}]}}, "training_config": {"loss": "binary_crossentropy", "metrics": [[{"class_name": "MeanMetricWrapper", "config": {"name": "accuracy", "dtype": "float32", "fn": "binary_accuracy"}, "shared_object_id": 11}]], "weighted_metrics": null, "loss_weights": null, "optimizer_config": {"class_name": "Custom>Adam", "config": {"name": "Adam", "weight_decay": null, "clipnorm": null, "global_clipnorm": null, "clipvalue": null, "use_ema": false, "ema_momentum": 0.99, "ema_overwrite_frequency": null, "jit_compile": false, "is_legacy_optimizer": false, "learning_rate": 0.0010000000474974513, "beta_1": 0.9, "beta_2": 0.999, "epsilon": 1e-07, "amsgrad": false}}}}2
+Ýroot.layer_with_weights-0"_tf_keras_rnn_layer*¢{"name": "lstm", "trainable": true, "expects_training_arg": true, "dtype": "float32", "batch_input_shape": null, "stateful": false, "must_restore_from_config": false, "preserve_input_structure_in_config": false, "autocast": true, "class_name": "LSTM", "config": {"name": "lstm", "trainable": true, "dtype": "float32", "return_sequences": false, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 32, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 1}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}, "shared_object_id": 2}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 3}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}, "shared_object_id": 5, "input_spec": [{"class_name": "InputSpec", "config": {"dtype": null, "shape": {"class_name": "__tuple__", "items": [null, null, 3]}, "ndim": 3, "max_ndim": null, "min_ndim": null, "axes": {}}, "shared_object_id": 12}], "build_input_shape": {"class_name": "TensorShape", "items": [null, 5, 3]}}2
+‚root.layer_with_weights-1"_tf_keras_layer*Ë{"name": "dense", "trainable": true, "expects_training_arg": false, "dtype": "float32", "batch_input_shape": null, "stateful": false, "must_restore_from_config": false, "preserve_input_structure_in_config": false, "autocast": true, "class_name": "Dense", "config": {"name": "dense", "trainable": true, "dtype": "float32", "units": 1, "activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 6}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 7}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}, "shared_object_id": 8, "input_spec": {"class_name": "InputSpec", "config": {"dtype": null, "shape": null, "ndim": null, "max_ndim": null, "min_ndim": 2, "axes": {"-1": 32}}, "shared_object_id": 13}, "build_input_shape": {"class_name": "TensorShape", "items": [null, 32]}}2
+ìroot.layer_with_weights-0.cell"_tf_keras_layer*°{"name": "lstm_cell", "trainable": true, "expects_training_arg": true, "dtype": "float32", "batch_input_shape": null, "stateful": false, "must_restore_from_config": false, "preserve_input_structure_in_config": false, "autocast": true, "class_name": "LSTMCell", "config": {"name": "lstm_cell", "trainable": true, "dtype": "float32", "units": 32, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 1}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}, "shared_object_id": 2}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 3}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}, "shared_object_id": 4, "build_input_shape": {"class_name": "__tuple__", "items": [null, 3]}}2
+¹Rroot.keras_api.metrics.0"_tf_keras_metric*‚{"class_name": "Mean", "name": "loss", "dtype": "float32", "config": {"name": "loss", "dtype": "float32"}, "shared_object_id": 14}2
+çSroot.keras_api.metrics.1"_tf_keras_metric*°{"class_name": "MeanMetricWrapper", "name": "accuracy", "dtype": "float32", "config": {"name": "accuracy", "dtype": "float32", "fn": "binary_accuracy"}, "shared_object_id": 11}2
\ No newline at end of file
diff --git a/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/saved_model.pb b/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/saved_model.pb
new file mode 100644
index 00000000..6fb7c3f0
Binary files /dev/null and b/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/saved_model.pb differ
diff --git a/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/variables/variables.data-00000-of-00001 b/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/variables/variables.data-00000-of-00001
new file mode 100644
index 00000000..83f2a2fc
Binary files /dev/null and b/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/variables/variables.data-00000-of-00001 differ
diff --git a/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/variables/variables.index b/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/variables/variables.index
new file mode 100644
index 00000000..ecdfe4d4
Binary files /dev/null and b/test/TensorFlowNET.Keras.UnitTest/Assets/lstm_from_sequential/variables/variables.index differ
diff --git a/test/TensorFlowNET.Keras.UnitTest/Model/ModelLoadTest.cs b/test/TensorFlowNET.Keras.UnitTest/Model/ModelLoadTest.cs
index 382941d9..299337cd 100644
--- a/test/TensorFlowNET.Keras.UnitTest/Model/ModelLoadTest.cs
+++ b/test/TensorFlowNET.Keras.UnitTest/Model/ModelLoadTest.cs
@@ -84,26 +84,12 @@ public class ModelLoadTest
     [TestMethod]
     public void LSTMLoad()
     {
-        var inputs = np.random.randn(10, 5, 3);
-        var outputs = np.random.randn(10, 1);
-        var model = keras.Sequential();
-        model.add(keras.Input(shape: (5, 3)));
-        var lstm = keras.layers.LSTM(32);
-
-        model.add(lstm);
-
-        model.add(keras.layers.Dense(1, keras.activations.Sigmoid));
-
-        model.compile(optimizer: keras.optimizers.Adam(),
-                    loss: keras.losses.MeanSquaredError(),
-        new[] { "accuracy" });
-
-        var result = model.fit(inputs.numpy(), outputs.numpy(), batch_size: 10, epochs: 3, workers: 16, use_multiprocessing: true);
-
-        model.save("LSTM_Random");
-
-        var model_loaded = keras.models.load_model("LSTM_Random");
-        model_loaded.summary();
+        var model = tf.keras.models.load_model(@"Assets/lstm_from_sequential");
+        model.summary();
+        model.compile(tf.keras.optimizers.Adam(), tf.keras.losses.MeanSquaredError(), new string[] { "accuracy" });
+        var inputs = tf.random.normal(shape: (10, 5, 3));
+        var outputs = tf.random.normal(shape: (10, 1));
+        model.fit(inputs.numpy(), outputs.numpy(), batch_size: 10, epochs: 5, workers: 16, use_multiprocessing: true);
     }
 
     [Ignore]
diff --git a/test/TensorFlowNET.Keras.UnitTest/Tensorflow.Keras.UnitTest.csproj b/test/TensorFlowNET.Keras.UnitTest/Tensorflow.Keras.UnitTest.csproj
index 58c176e8..3910eba1 100644
--- a/test/TensorFlowNET.Keras.UnitTest/Tensorflow.Keras.UnitTest.csproj
+++ b/test/TensorFlowNET.Keras.UnitTest/Tensorflow.Keras.UnitTest.csproj
@@ -65,6 +65,22 @@
     <None Update="Assets\python_func_model\variables\variables.index">
       <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
     </None>
+
+    <None Update="Assets\lstm_from_sequential\fingerprint.pb">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+    <None Update="Assets\lstm_from_sequential\keras_metadata.pb">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+    <None Update="Assets\lstm_from_sequential\saved_model.pb">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+    <None Update="Assets\lstm_from_sequential\variables\variables.data-00000-of-00001">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
+    <None Update="Assets\lstm_from_sequential\variables\variables.index">
+      <CopyToOutputDirectory>PreserveNewest</CopyToOutputDirectory>
+    </None>
   </ItemGroup>
 
 </Project>
