diff --git a/docs/guides/deploy_local_llm.md b/docs/guides/deploy_local_llm.md
index 8b184e3af..1326125b3 100644
--- a/docs/guides/deploy_local_llm.md
+++ b/docs/guides/deploy_local_llm.md
@@ -236,32 +236,28 @@ You may launch the Ollama service as below:
   ollama serve
   ```
 
-> [!NOTE]
+
 > Please set environment variable `OLLAMA_NUM_GPU` to `999` to make sure all layers of your model are running on Intel GPU, otherwise, some layers may run on CPU.
 
-> [!TIP]
+
 > If your local LLM is running on Intel Arc™ A-Series Graphics with Linux OS (Kernel 6.2), it is recommended to additionaly set the following environment variable for optimal performance before executing `ollama serve`:
 >
 > ```bash
 > export SYCL_PI_LEVEL_ZERO_USE_IMMEDIATE_COMMANDLISTS=1
 > ```
 
-> [!NOTE]
+
 > To allow the service to accept connections from all IP addresses, use `OLLAMA_HOST=0.0.0.0 ./ollama serve` instead of just `./ollama serve`.
 
 The console will display messages similar to the following:
 
-<a href="https://llm-assets.readthedocs.io/en/latest/_images/ollama_serve.png" target="_blank">
-  <img src="https://llm-assets.readthedocs.io/en/latest/_images/ollama_serve.png" width=100%; />
-</a>
+![](https://llm-assets.readthedocs.io/en/latest/_images/ollama_serve.png)
 
 ### 3. Pull and Run Ollama Model
 
 Keep the Ollama service on and open another terminal and run `./ollama pull <model_name>` in Linux (`ollama.exe pull <model_name>` in Windows) to automatically pull a model. e.g. `qwen2:latest`:
 
-<a href="https://llm-assets.readthedocs.io/en/latest/_images/ollama_pull.png" target="_blank">
-  <img src="https://llm-assets.readthedocs.io/en/latest/_images/ollama_pull.png" width=100%; />
-</a>
+![](https://llm-assets.readthedocs.io/en/latest/_images/ollama_pull.png)
 
 #### Run Ollama Model