diff --git a/examples/ollama/README.md b/examples/ollama/README.md
new file mode 100644
index 0000000..3b28d19
--- /dev/null
+++ b/examples/ollama/README.md
@@ -0,0 +1,39 @@
+# Running a Local Ollama Model
+
+## Dependencies
+
+- ollama
+- litellm
+- setuptools
+
+## Instructions
+
+1. Install Ollama by visiting the website [https://ollama.ai/download](https://ollama.ai/download) and selecting the appropriate operating system.
+
+2. Once installed, open the Ollama app, which should be running in your taskbar.
+
+3. Open the terminal and download a model. For example, to download the llama2 model, run the command:
+
+```bash
+ollama run llama2
+```
+
+4. In your terminal, start your virtual environment and install the 'litellm[proxy]' package using poetry you can run the command:
+
+```bash
+poetry add 'litellm[proxy]'
+```
+
+5. Next, install setuptools using the command:
+
+```bash
+poetry add setuptools
+```
+
+6. Lastly, start the litellm server with the command: `litellm --model ollama/llama2`. This will expose the port on your local machine.
+
+```bash
+litellm --model ollama/llama2
+```
+
+7. Now you can run the completion!
diff --git a/examples/ollama/run.py b/examples/ollama/run.py
new file mode 100644
index 0000000..4fa69e3
--- /dev/null
+++ b/examples/ollama/run.py
@@ -0,0 +1,35 @@
+from litellm import completion, provider_list
+from pydantic import BaseModel
+
+import instructor
+from instructor.patch import wrap_chatcompletion
+
+completion = wrap_chatcompletion(func=completion, mode=instructor.Mode.MD_JSON)
+
+
+class UserExtract(BaseModel):
+    name: str
+    age: int
+
+
+user = completion(
+    model="ollama/llama2",
+    response_model=UserExtract,
+    messages=[
+        {
+            "role": "system",
+            "content": "You are a JSON extractor. Please extract the following JSON, No Talk. You must return JSON right after the Codeblock",
+        },
+        {
+            "role": "user",
+            "content": "Extract `My name is Jason and I am 25 years old`",
+        },
+    ],
+)
+
+print(user.model_dump_json(indent=2))
+assert isinstance(user, UserExtract), "Should be instance of UserExtract"
+assert user.name.lower() == "jason"
+assert user.age == 25
+assert hasattr(user, "_raw_response")
+assert any(provider in user._raw_response.model for provider in provider_list)
diff --git a/instructor/patch.py b/instructor/patch.py
index f15109d..968c0ed 100644
--- a/instructor/patch.py
+++ b/instructor/patch.py
@@ -119,7 +119,7 @@ def handle_response_model(
                 new_kwargs["messages"].append(
                     {
                         "role": "assistant",
-                        "content": "```json",
+                        "content": "Here is the perfectly correctly formatted JSON\n```json",
                     },
                 )
                 new_kwargs["stop"] = "```"