diff --git a/text-generation-inference/tests/integration/test_generate.py b/text-generation-inference/tests/integration/test_generate.py
index 6f5659401..0a6abf649 100644
--- a/text-generation-inference/tests/integration/test_generate.py
+++ b/text-generation-inference/tests/integration/test_generate.py
@@ -1,39 +1,15 @@
-import os
 
 import Levenshtein
 import pytest
 
 
-@pytest.fixture(params=["hub-neuron", "hub", "local-neuron"])
-async def tgi_service(request, launcher, neuron_model_config):
-    """Expose a TGI service corresponding to a model configuration
-
-    For each model configuration, the service will be started using the following
-    deployment options:
-    - from the hub original model (export parameters specified as env variables),
-    - from the hub pre-exported neuron model,
-    - from a local path to the neuron model.
-    """
-    if request.param == "hub":
-        export_kwargs = neuron_model_config["export_kwargs"]
-        # Expose export parameters as environment variables
-        for kwarg, value in export_kwargs.items():
-            env_var = f"HF_{kwarg.upper()}"
-            os.environ[env_var] = str(value)
-        model_name_or_path = neuron_model_config["model_id"]
-    elif request.param == "hub-neuron":
-        model_name_or_path = neuron_model_config["neuron_model_id"]
-    else:
-        model_name_or_path = neuron_model_config["neuron_model_path"]
+@pytest.fixture
+async def tgi_service(launcher, neuron_model_config):
+    model_name_or_path = neuron_model_config["neuron_model_path"]
     service_name = neuron_model_config["name"]
     with launcher(service_name, model_name_or_path) as tgi_service:
         await tgi_service.health(600)
         yield tgi_service
-    if request.param == "hub":
-        # Cleanup export parameters
-        for kwarg in export_kwargs:
-            env_var = f"HF_{kwarg.upper()}"
-            del os.environ[env_var]
 
 
 @pytest.mark.asyncio