diff --git a/doc_generator/main.py b/doc_generator/main.py
index 5770a2d..bae7744 100644
--- a/doc_generator/main.py
+++ b/doc_generator/main.py
@@ -53,6 +53,14 @@ def main():  # pragma: no cover
     #      LLMModels.GOOGLE_GEMMA_7B_INSTRUCT.value])
     model_name = prompt("Which model?\n")
     match model_name:
+        case LLMModels.LLAMA2_7B_CHAT_GPTQ.value:
+            model = LLMModels.LLAMA2_7B_CHAT_GPTQ
+        case LLMModels.LLAMA2_13B_CHAT_GPTQ.value:
+            model = LLMModels.LLAMA2_13B_CHAT_GPTQ
+        case LLMModels.CODELLAMA_7B_INSTRUCT_GPTQ.value:
+            model = LLMModels.CODELLAMA_7B_INSTRUCT_GPTQ
+        case LLMModels.CODELLAMA_13B_INSTRUCT_GPTQ.value:
+            model = LLMModels.CODELLAMA_13B_INSTRUCT_GPTQ
         case LLMModels.LLAMA2_13B_CHAT_HF.value:
             model = LLMModels.LLAMA2_13B_CHAT_HF
         case LLMModels.CODELLAMA_7B_INSTRUCT_HF.value:
diff --git a/doc_generator/utils/llm_utils.py b/doc_generator/utils/llm_utils.py
index 612c454..fb8c7f3 100644
--- a/doc_generator/utils/llm_utils.py
+++ b/doc_generator/utils/llm_utils.py
@@ -154,21 +154,21 @@ def get_tokenizer(model_name: str):
         failed=0,
         total=0,
     ),
-    # LLMModels.LLAMA2_7B_CHAT_GPTQ: LLMModelDetails(
-    #     name=LLMModels.LLAMA2_7B_CHAT_GPTQ,
-    #     input_cost_per_1k_tokens=0,
-    #     output_cost_per_1k_tokens=0,
-    #     max_length=4096,
-    #     llm=get_llama_chat_model(
-    #         LLMModels.LLAMA2_7B_CHAT_GPTQ.value,
-    #         model_kwargs={"temperature": 0}
-    #     ),
-    #     input_tokens=0,
-    #     output_tokens=0,
-    #     succeeded=0,
-    #     failed=0,
-    #     total=0,
-    # ),
+    LLMModels.LLAMA2_7B_CHAT_GPTQ: LLMModelDetails(
+        name=LLMModels.LLAMA2_7B_CHAT_GPTQ,
+        input_cost_per_1k_tokens=0,
+        output_cost_per_1k_tokens=0,
+        max_length=4096,
+        llm=get_llama_chat_model(
+            LLMModels.LLAMA2_7B_CHAT_GPTQ.value,
+            model_kwargs={"temperature": 0}
+        ),
+        input_tokens=0,
+        output_tokens=0,
+        succeeded=0,
+        failed=0,
+        total=0,
+    ),
     # LLMModels.LLAMA2_13B_CHAT_GPTQ: LLMModelDetails(
     #     name=LLMModels.LLAMA2_13B_CHAT_GPTQ,
     #     input_cost_per_1k_tokens=0,
@@ -274,21 +274,21 @@ def get_tokenizer(model_name: str):
     #     failed=0,
     #     total=0,
     # ),
-    LLMModels.GOOGLE_GEMMA_2B_INSTRUCT: LLMModelDetails(
-        name=LLMModels.GOOGLE_GEMMA_2B_INSTRUCT,
-        input_cost_per_1k_tokens=0,
-        output_cost_per_1k_tokens=0,
-        max_length=8192,
-        llm=get_gemma_chat_model(
-            LLMModels.GOOGLE_GEMMA_2B_INSTRUCT.value,
-            model_kwargs={"temperature": 0}
-        ),
-        input_tokens=0,
-        output_tokens=0,
-        succeeded=0,
-        failed=0,
-        total=0,
-    ),
+    # LLMModels.GOOGLE_GEMMA_2B_INSTRUCT: LLMModelDetails(
+    #     name=LLMModels.GOOGLE_GEMMA_2B_INSTRUCT,
+    #     input_cost_per_1k_tokens=0,
+    #     output_cost_per_1k_tokens=0,
+    #     max_length=8192,
+    #     llm=get_gemma_chat_model(
+    #         LLMModels.GOOGLE_GEMMA_2B_INSTRUCT.value,
+    #         model_kwargs={"temperature": 0}
+    #     ),
+    #     input_tokens=0,
+    #     output_tokens=0,
+    #     succeeded=0,
+    #     failed=0,
+    #     total=0,
+    # ),
     # LLMModels.GOOGLE_GEMMA_7B_INSTRUCT: LLMModelDetails(
     #     name=LLMModels.GOOGLE_GEMMA_7B_INSTRUCT,
     #     input_cost_per_1k_tokens=0,