[Lint]Style: reformat markdown files via markdownlint (#5884)

### What this PR does / why we need it?
reformat markdown files via markdownlint

- vLLM version: v0.13.0
- vLLM main:
bde38c11df

---------

Signed-off-by: root <root@LAPTOP-VQKDDVMG.localdomain>
Signed-off-by: MrZ20 <2609716663@qq.com>
Co-authored-by: root <root@LAPTOP-VQKDDVMG.localdomain>

docs/source/tutorials/Qwen-VL-Dense.md

@@ -19,6 +19,7 @@ Refer to [feature guide](../user_guide/feature_guide/index.md) to get the featur
 ### Model Weight
 
 require 1 Atlas 800I A2 (64G × 8) node or 1 Atlas 800 A3 (64G × 16) node:
+
 - `Qwen2.5-VL-3B-Instruct`: [Download model weight](https://modelscope.cn/models/Qwen/Qwen2.5-VL-3B-Instruct)
 - `Qwen2.5-VL-7B-Instruct`: [Download model weight](https://modelscope.cn/models/Qwen/Qwen2.5-VL-7B-Instruct)
 - `Qwen2.5-VL-32B-Instruct`:[Download model weight](https://modelscope.cn/models/Qwen/Qwen2.5-VL-32B-Instruct)
@@ -188,7 +189,7 @@ print(generated_text)
 
 If you run this script successfully, you can see the info shown below:
 
-```
+```shell
 **Visual Components:**
 
 1.  **Abstract Geometric Icon (Left Side):**
@@ -284,7 +285,7 @@ print(generated_text)
 
 If you run this script successfully, you can see the info shown below:
 
-```
+```shell
 The image displays a logo and text related to the Qwen model, which is an artificial intelligence (AI) language model developed by Alibaba Cloud. Here is a detailed description of the elements in the image:
 
 ### **1. Logo:**
@@ -469,6 +470,7 @@ INFO 12-05 08:51:20 [loggers.py:127] Engine 000: Avg prompt throughput: 0.0 toke
 ### Using Language Model Evaluation Harness
 
 The accuracy of some models is already within our CI monitoring scope, including:
+
 - `Qwen2.5-VL-7B-Instruct`
 - `Qwen3-VL-8B-Instruct`
 
@@ -547,6 +549,7 @@ lm_eval \
 Refer to [vllm benchmark](https://docs.vllm.ai/en/latest/contributing/benchmarks.html) for more details.
 
 There are three `vllm bench` subcommand:
+
 - `latency`: Benchmark the latency of a single batch of requests.
 - `serve`: Benchmark the online serving throughput.
 - `throughput`: Benchmark offline inference throughput.