diff --git a/generative_ai/list_tuned_code_generation_models.py b/generative_ai/list_tuned_code_generation_models.py
new file mode 100644
index 00000000000..c9e2ea85f8e
--- /dev/null
+++ b/generative_ai/list_tuned_code_generation_models.py
@@ -0,0 +1,35 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# [START aiplatform_sdk_list_tuned_code_generation_models]
+
+import vertexai
+from vertexai.preview.language_models import CodeGenerationModel
+
+
+def list_tuned_code_generation_models(
+    project_id: str,
+    location: str,
+) -> None:
+    """List tuned models."""
+    vertexai.init(project=project_id, location=location)
+    model = CodeGenerationModel.from_pretrained("code-bison@001")
+    tuned_model_names = model.list_tuned_model_names()
+    print(tuned_model_names)
+    # [END aiplatform_sdk_list_tuned_code_generation_models]
+    return tuned_model_names
+
+
+if __name__ == "__main__":
+    list_tuned_code_generation_models()
diff --git a/generative_ai/list_tuned_code_generation_models_test.py b/generative_ai/list_tuned_code_generation_models_test.py
new file mode 100644
index 00000000000..624cb8ade3a
--- /dev/null
+++ b/generative_ai/list_tuned_code_generation_models_test.py
@@ -0,0 +1,42 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+import backoff
+from google.api_core.exceptions import ResourceExhausted
+from google.cloud import aiplatform
+
+import list_tuned_code_generation_models
+
+
+_PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
+_LOCATION = "us-central1"
+
+
+@backoff.on_exception(backoff.expo, ResourceExhausted, max_time=10)
+def test_list_tuned_code_generation_models() -> None:
+    tuned_model_names = list_tuned_code_generation_models.list_tuned_code_generation_models(
+        _PROJECT_ID,
+        _LOCATION,
+    )
+    filtered_models_counter = 0
+    for tuned_model_name in tuned_model_names:
+        model_registry = aiplatform.models.ModelRegistry(model=tuned_model_name)
+        if (
+            "Vertex LLM Test Fixture "
+            "(list_tuned_models_test.py::test_list_tuned_models)"
+        ) in model_registry.get_version_info("1").model_display_name:
+            filtered_models_counter += 1
+    assert filtered_models_counter == 0
diff --git a/generative_ai/requirements.txt b/generative_ai/requirements.txt
index 3f2377d0986..f1d40be161b 100644
--- a/generative_ai/requirements.txt
+++ b/generative_ai/requirements.txt
@@ -1,4 +1,4 @@
 pandas==1.3.5; python_version == '3.7'
 pandas==2.0.1; python_version > '3.7'
-google-cloud-aiplatform[pipelines]==1.28.1
+google-cloud-aiplatform[pipelines]==1.29.0
 google-auth==2.17.3
diff --git a/generative_ai/tune_code_generation_model.py b/generative_ai/tune_code_generation_model.py
new file mode 100644
index 00000000000..4474f7ea8fa
--- /dev/null
+++ b/generative_ai/tune_code_generation_model.py
@@ -0,0 +1,70 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# [START aiplatform_sdk_tune_code_generation_model]
+from __future__ import annotations
+
+
+from google.auth import default
+import pandas as pd
+import vertexai
+from vertexai.preview.language_models import CodeGenerationModel
+
+credentials, _ = default(scopes=["https://www.googleapis.com/auth/cloud-platform"])
+
+
+def tune_code_generation_model(
+    project_id: str,
+    location: str,
+    training_data: pd.DataFrame | str,
+    train_steps: int = 300,
+) -> None:
+    """Tune a new model, based on a prompt-response data.
+
+    "training_data" can be either the GCS URI of a file formatted in JSONL format
+    (for example: training_data=f'gs://{bucket}/{filename}.jsonl'), or a pandas
+    DataFrame. Each training example should be JSONL record with two keys, for
+    example:
+      {
+        "input_text": <input prompt>,
+        "output_text": <associated output>
+      },
+    or the pandas DataFame should contain two columns:
+      ['input_text', 'output_text']
+    with rows for each training example.
+
+    Args:
+      project_id: GCP Project ID, used to initialize vertexai
+      location: GCP Region, used to initialize vertexai
+      training_data: GCS URI of jsonl file or pandas dataframe of training data
+      train_steps: Number of training steps to use when tuning the model.
+    """
+    vertexai.init(project=project_id, location=location, credentials=credentials)
+    model = CodeGenerationModel.from_pretrained("code-bison@001")
+
+    model.tune_model(
+        training_data=training_data,
+        # Optional:
+        train_steps=train_steps,
+        tuning_job_location="europe-west4",
+        tuned_model_location=location,
+    )
+
+    print(model._job.status)
+    # [END aiplatform_sdk_tune_code_generation_model]
+    return model
+
+
+if __name__ == "__main__":
+    tune_code_generation_model()
diff --git a/generative_ai/tune_code_generation_model_test.py b/generative_ai/tune_code_generation_model_test.py
new file mode 100644
index 00000000000..ccd4888f974
--- /dev/null
+++ b/generative_ai/tune_code_generation_model_test.py
@@ -0,0 +1,107 @@
+# Copyright 2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import uuid
+
+from google.cloud import aiplatform
+from google.cloud import storage
+from google.cloud.aiplatform.compat.types import pipeline_state
+import pytest
+from vertexai.preview.language_models import TextGenerationModel
+
+import tune_code_generation_model
+
+_PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
+_LOCATION = "us-central1"
+_BUCKET = os.environ["CLOUD_STORAGE_BUCKET"]
+
+
+def get_model_display_name(tuned_model: TextGenerationModel) -> str:
+    language_model_tuning_job = tuned_model._job
+    pipeline_job = language_model_tuning_job._job
+    return dict(pipeline_job._gca_resource.runtime_config.parameter_values)[
+        "model_display_name"
+    ]
+
+
+def upload_to_gcs(bucket: str, name: str, data: str) -> None:
+    client = storage.Client()
+    bucket = client.get_bucket(bucket)
+    blob = bucket.blob(name)
+    blob.upload_from_string(data)
+
+
+def download_from_gcs(bucket: str, name: str) -> str:
+    client = storage.Client()
+    bucket = client.get_bucket(bucket)
+    blob = bucket.blob(name)
+    data = blob.download_as_bytes()
+    return "\n".join(data.decode().splitlines()[:10])
+
+
+def delete_from_gcs(bucket: str, name: str) -> None:
+    client = storage.Client()
+    bucket = client.get_bucket(bucket)
+    blob = bucket.blob(name)
+    blob.delete()
+
+
+@pytest.fixture(scope="function")
+def training_data_filename() -> str:
+    temp_filename = f"{uuid.uuid4()}.jsonl"
+    data = download_from_gcs(
+        "cloud-samples-data", "ai-platform/generative_ai/headline_classification.jsonl"
+    )
+    upload_to_gcs(_BUCKET, temp_filename, data)
+    try:
+        yield f"gs://{_BUCKET}/{temp_filename}"
+    finally:
+        delete_from_gcs(_BUCKET, temp_filename)
+
+
+def teardown_model(
+    tuned_model: TextGenerationModel, training_data_filename: str
+) -> None:
+    for tuned_model_name in tuned_model.list_tuned_model_names():
+        model_registry = aiplatform.models.ModelRegistry(model=tuned_model_name)
+        if (
+            training_data_filename
+            in model_registry.get_version_info("1").model_display_name
+        ):
+            display_name = model_registry.get_version_info("1").model_display_name
+            for endpoint in aiplatform.Endpoint.list():
+                for _ in endpoint.list_models():
+                    if endpoint.display_name == display_name:
+                        endpoint.undeploy_all()
+                        endpoint.delete()
+            aiplatform.Model(model_registry.model_resource_name).delete()
+
+
+@pytest.mark.skip("Blocked on b/277959219")
+def test_tuning_code_generation_model(training_data_filename: str) -> None:
+    """Takes approx. 20 minutes."""
+    tuned_model = tune_code_generation_model.tune_code_generation_model(
+        training_data=training_data_filename,
+        project_id=_PROJECT_ID,
+        location=_LOCATION,
+        train_steps=1,
+    )
+    try:
+        assert (
+            tuned_model._job.status
+            == pipeline_state.PipelineState.PIPELINE_STATE_SUCCEEDED
+        )
+    finally:
+        teardown_model(tuned_model, training_data_filename)