diff --git a/litellm/llms/prompt_templates/factory.py b/litellm/llms/prompt_templates/factory.py
index 4b616b785bc..38bc0703fcc 100644
--- a/litellm/llms/prompt_templates/factory.py
+++ b/litellm/llms/prompt_templates/factory.py
@@ -29,25 +29,29 @@ def llama_2_chat_pt(messages):
     )
     return prompt
 
-def ollama_pt(messages): # https://github.com/jmorganca/ollama/blob/af4cf55884ac54b9e637cd71dadfe9b7a5685877/docs/modelfile.md#template
-    prompt = custom_prompt(
-        role_dict={
-            "system": {
-                "pre_message": "### System:\n",
-                "post_message": "\n"
-            }, 
-            "user": {
-                "pre_message": "### User:\n",
-                "post_message": "\n",
-            }, 
-            "assistant": {
-                "pre_message": "### Response:\n",
-                "post_message": "\n",
-            }
-        },
-        final_prompt_value="### Response:",
-        messages=messages
-    )
+def ollama_pt(model, messages): # https://github.com/jmorganca/ollama/blob/af4cf55884ac54b9e637cd71dadfe9b7a5685877/docs/modelfile.md#template
+    
+    if "instruct" in model: 
+        prompt = custom_prompt(
+            role_dict={
+                "system": {
+                    "pre_message": "### System:\n",
+                    "post_message": "\n"
+                }, 
+                "user": {
+                    "pre_message": "### User:\n",
+                    "post_message": "\n",
+                }, 
+                "assistant": {
+                    "pre_message": "### Response:\n",
+                    "post_message": "\n",
+                }
+            },
+            final_prompt_value="### Response:",
+            messages=messages
+        )
+    else: 
+        prompt = "".join(m["content"] for m in messages)
     return prompt
 
 def mistral_instruct_pt(messages): 
@@ -274,7 +278,7 @@ def prompt_factory(model: str, messages: list, custom_llm_provider: Optional[str
     model = model.lower()
 
     if custom_llm_provider == "ollama": 
-        return ollama_pt(messages=messages)
+        return ollama_pt(model=model, messages=messages)
     elif custom_llm_provider == "anthropic":
         return anthropic_pt(messages=messages)