diff --git a/src/synthetic_dataset_generator/pipelines/textcat.py b/src/synthetic_dataset_generator/pipelines/textcat.py
index deefe78..4f5f11d 100644
--- a/src/synthetic_dataset_generator/pipelines/textcat.py
+++ b/src/synthetic_dataset_generator/pipelines/textcat.py
@@ -171,6 +171,8 @@ def generate_pipeline_code(
     temperature: float = 0.9,
 ) -> str:
     labels = get_preprocess_labels(labels)
+    MODEL_ARG = "model_id" if BASE_URL else "model"
+    MODEL_CLASS = "InferenceEndpointsLLM" if BASE_URL else "OpenAILLM"
     base_code = f"""
 # Requirements: `pip install distilabel[hf-inference-endpoints]`
 import os
@@ -192,15 +194,13 @@ def generate_pipeline_code(
     task_generator = LoadDataFromDicts(data=[{{"task": TEXT_CLASSIFICATION_TASK}}])
 
     textcat_generation = GenerateTextClassificationData(
-        llm=InferenceEndpointsLLM(
-            model_id=MODEL,
+        llm={MODEL_CLASS}(
+            {MODEL_ARG}=MODEL,
             base_url=BASE_URL,
             api_key=os.environ["API_KEY"],
             generation_kwargs={{
                 "temperature": {temperature},
                 "max_new_tokens": {MAX_NUM_TOKENS},
-                "do_sample": True,
-                "top_k": 50,
                 "top_p": 0.95,
             }},
         ),
@@ -236,8 +236,8 @@ def generate_pipeline_code(
     )
 
     textcat_labeller = TextClassification(
-        llm=InferenceEndpointsLLM(
-            model_id=MODEL,
+        llm={MODEL_CLASS}(
+            {MODEL_ARG}=MODEL,
             base_url=BASE_URL,
             api_key=os.environ["API_KEY"],
             generation_kwargs={{