diff --git a/src/sparseml/transformers/integration_helper_functions_generative.py b/src/sparseml/transformers/integration_helper_functions_generative.py
new file mode 100644
index 00000000000..2c17f47395a
--- /dev/null
+++ b/src/sparseml/transformers/integration_helper_functions_generative.py
@@ -0,0 +1,44 @@
+# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
+#
+# 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
+#
+#    http://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.
+
+
+from typing import Callable, Dict, List
+
+from pydantic import Field
+
+from sparseml.transformers.integration_helper_functions import Transformers
+from sparseml.transformers.utils.helpers import (
+    MANDATORY_DEPLOYMENT_FILES,
+    NLG_TOKENIZER_FILES,
+)
+from sparseml.transformers.utils.optimizations import apply_kv_cache_injection
+from src.sparseml.integration_helper_functions import (
+    IntegrationHelperFunctions,
+    Integrations,
+)
+
+
+generative_transformers_graph_optimizations = {
+    "kv_cache_injection": apply_kv_cache_injection
+}
+
+
+@IntegrationHelperFunctions.register(name=Integrations.transformers_generative.value)
+class GenerativeTransformers(Transformers):
+    graph_optimizations: Dict[str, Callable] = Field(
+        default=generative_transformers_graph_optimizations
+    )
+    deployment_directory_files_mandatory: List[str] = Field(
+        default=list(MANDATORY_DEPLOYMENT_FILES.union(NLG_TOKENIZER_FILES))
+    )
diff --git a/src/sparseml/transformers/utils/optimizations.py b/src/sparseml/transformers/utils/optimizations.py
new file mode 100644
index 00000000000..20b58775b10
--- /dev/null
+++ b/src/sparseml/transformers/utils/optimizations.py
@@ -0,0 +1,41 @@
+# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
+#
+# 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
+#
+#    http://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 logging
+import os
+from pathlib import Path
+from typing import Union
+
+import onnx
+
+from sparseml.exporters.kv_cache_injector import KeyValueCacheInjector
+
+
+__all__ = ["apply_kv_cache_injection"]
+
+_LOGGER = logging.getLogger(__name__)
+
+
+def apply_kv_cache_injection(onnx_model_path: Union[str, Path]) -> bool:
+    """
+    Apply key value cache injection to an ONNX model
+
+    :param onnx_model_path: path to the ONNX model to inject
+    :return: True if successful, False otherwise
+    """
+    onnx_model = onnx.load(onnx_model_path, load_external_data=False)
+    model_path = os.path.dirname(onnx_model_path)
+    exporter = KeyValueCacheInjector(model_path=model_path)
+    exporter.export(onnx_model, onnx_model_path)
+    return True
diff --git a/tests/sparseml/export/transformers/test_generative_transformers.py b/tests/sparseml/export/transformers/test_generative_transformers.py
new file mode 100644
index 00000000000..8a014360fee
--- /dev/null
+++ b/tests/sparseml/export/transformers/test_generative_transformers.py
@@ -0,0 +1,79 @@
+# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
+#
+# 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
+#
+#    http://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 shutil
+
+import pytest
+import torch
+
+from huggingface_hub import snapshot_download
+from sparseml.export.export import export
+
+
+@pytest.mark.parametrize(
+    "stub, task",
+    [("roneneldan/TinyStories-1M", "text-generation")],
+)
+class TestEndToEndExport:
+    @pytest.fixture()
+    def setup(self, tmp_path, stub, task):
+        model_path = tmp_path / "model"
+        target_path = tmp_path / "target"
+
+        source_path = snapshot_download(stub, local_dir=model_path)
+
+        yield source_path, target_path, task
+
+        shutil.rmtree(tmp_path)
+
+    def test_export_happy_path(self, setup):
+        source_path, target_path, task = setup
+        export(
+            source_path=source_path,
+            target_path=target_path,
+            task=task,
+        )
+        assert (target_path / "deployment" / "model.onnx").exists()
+
+    def test_export_with_sample_data(self, setup):
+        source_path, target_path, task = setup
+
+        sequence_length = 32
+        sample_data = dict(
+            input_ids=torch.ones((10, sequence_length), dtype=torch.long),
+            attention_mask=torch.ones((10, sequence_length), dtype=torch.long),
+        )
+        export(
+            source_path=source_path,
+            target_path=target_path,
+            task=task,
+            sample_data=sample_data,
+        )
+        assert (target_path / "deployment" / "model.onnx").exists()
+
+    @pytest.mark.skipif(
+        reason="skipping since this functionality needs some more attention"
+    )
+    def test_export_validate_correctness(self, setup):
+        source_path, target_path, task = setup
+
+        num_samples = 4
+
+        export(
+            source_path=source_path,
+            target_path=target_path,
+            task=task,
+            num_export_samples=num_samples,
+            validate_correctness=True,
+        )
diff --git a/tests/sparseml/transformers/test_integration_helper_functions_generative.py b/tests/sparseml/transformers/test_integration_helper_functions_generative.py
new file mode 100644
index 00000000000..7a1c77f7066
--- /dev/null
+++ b/tests/sparseml/transformers/test_integration_helper_functions_generative.py
@@ -0,0 +1,43 @@
+# Copyright (c) 2021 - present / Neuralmagic, Inc. All Rights Reserved.
+#
+# 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
+#
+#    http://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.
+from src.sparseml.integration_helper_functions import (
+    IntegrationHelperFunctions,
+    Integrations,
+)
+
+
+def test_integration_helper_functions():
+    # import needed to register the object on the fly
+    import sparseml.transformers.integration_helper_functions_generative  # noqa F401
+
+    transformers_gen = IntegrationHelperFunctions.load_from_registry(
+        Integrations.transformers_generative.value
+    )
+    assert transformers_gen.create_model
+    assert transformers_gen.create_dummy_input
+    assert transformers_gen.export
+    assert transformers_gen.graph_optimizations.values() == ["apply_kv_cache_injection"]
+    assert transformers_gen.create_data_samples
+    assert set(transformers_gen.deployment_directory_files_mandatory) == {
+        "model.onnx",
+        "tokenizer_config.json",
+        "config.json",
+        "special_tokens_map.json",
+        "vocab.json",
+        "merges.txt",
+    }
+    assert set(transformers_gen.deployment_directory_files_optional) == {
+        "tokenizer.json",
+        "tokenizer.model",
+    }