Allow markdownlint to run locally (#36398)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

docs/getting_started/installation/gpu.xpu.inc.md

@@ -1,29 +1,30 @@
-# --8<-- [start:installation]
+<!-- markdownlint-disable MD041 -->
+--8<-- [start:installation]
 
 vLLM initially supports basic model inference and serving on Intel GPU platform.
 
-# --8<-- [end:installation]
-# --8<-- [start:requirements]
+--8<-- [end:installation]
+--8<-- [start:requirements]
 
 - Supported Hardware: Intel Data Center GPU, Intel ARC GPU
 - OneAPI requirements: oneAPI 2025.3
-- Dependency: [vllm-xpu-kernels](https://github.com/vllm-project/vllm-xpu-kernels): a package provide all necessary vllm custom kernel when running vLLM on Intel GPU platform, 
+- Dependency: [vllm-xpu-kernels](https://github.com/vllm-project/vllm-xpu-kernels): a package provide all necessary vllm custom kernel when running vLLM on Intel GPU platform,
 - Python: 3.12
 !!! warning
     The provided vllm-xpu-kernels whl is Python3.12 specific so this version is a MUST.
 
-# --8<-- [end:requirements]
-# --8<-- [start:set-up-using-python]
+--8<-- [end:requirements]
+--8<-- [start:set-up-using-python]
 
 There is no extra information on creating a new Python environment for this device.
 
-# --8<-- [end:set-up-using-python]
-# --8<-- [start:pre-built-wheels]
+--8<-- [end:set-up-using-python]
+--8<-- [start:pre-built-wheels]
 
 Currently, there are no pre-built XPU wheels.
 
-# --8<-- [end:pre-built-wheels]
-# --8<-- [start:build-wheel-from-source]
+--8<-- [end:pre-built-wheels]
+--8<-- [start:build-wheel-from-source]
 
 - First, install required [driver](https://dgpu-docs.intel.com/driver/installation.html#installing-gpu-drivers) and [Intel OneAPI](https://www.intel.com/content/www/us/en/developer/tools/oneapi/base-toolkit.html) 2025.3 or later.
 - Second, install Python packages for vLLM XPU backend building:
@@ -54,13 +55,13 @@ pip install -v -r requirements/xpu.txt
 VLLM_TARGET_DEVICE=xpu pip install --no-build-isolation -e . -v
 ```
 
-# --8<-- [end:build-wheel-from-source]
-# --8<-- [start:pre-built-images]
+--8<-- [end:build-wheel-from-source]
+--8<-- [start:pre-built-images]
 
 Currently, we release prebuilt XPU images at docker [hub](https://hub.docker.com/r/intel/vllm/tags) based on vLLM released version. For more information, please refer release [note](https://github.com/intel/ai-containers/blob/main/vllm).
 
-# --8<-- [end:pre-built-images]
-# --8<-- [start:build-image-from-source]
+--8<-- [end:pre-built-images]
+--8<-- [start:build-image-from-source]
 
 ```bash
 docker build -f docker/Dockerfile.xpu -t vllm-xpu-env --shm-size=4g .
@@ -74,8 +75,8 @@ docker run -it \
              vllm-xpu-env
 ```
 
-# --8<-- [end:build-image-from-source]
-# --8<-- [start:supported-features]
+--8<-- [end:build-image-from-source]
+--8<-- [start:supported-features]
 
 XPU platform supports **tensor parallel** inference/serving and also supports **pipeline parallel** as a beta feature for online serving. For **pipeline parallel**, we support it on single node with mp as the backend. For example, a reference execution like following:
 
@@ -90,9 +91,9 @@ vllm serve facebook/opt-13b \
 
 By default, a ray instance will be launched automatically if no existing one is detected in the system, with `num-gpus` equals to `parallel_config.world_size`. We recommend properly starting a ray cluster before execution, referring to the [examples/online_serving/run_cluster.sh](https://github.com/vllm-project/vllm/blob/main/examples/online_serving/run_cluster.sh) helper script.
 
-# --8<-- [end:supported-features]
-# --8<-- [start:distributed-backend]
+--8<-- [end:supported-features]
+--8<-- [start:distributed-backend]
 
 XPU platform uses **torch-ccl** for torch<2.8 and **xccl** for torch>=2.8 as distributed backend, since torch 2.8 supports **xccl** as built-in backend for XPU.
 
-# --8<-- [end:distributed-backend]
+--8<-- [end:distributed-backend]