[Doc][Misc] Improve documentation quality by revising specific content. (#8603)

### What this PR does / why we need it?

To improve the quality of certain docs by revising specific content.

### Does this PR introduce _any_ user-facing change?

None

### How was this patch tested?

- vLLM version: v0.19.0
- vLLM main:
6f786f2c50

---------

Signed-off-by: Lucky1 <144669645+verylucky01@users.noreply.github.com>

docs/source/developer_guide/contribution/testing.md

@@ -23,7 +23,7 @@ cd ~/vllm-project/
 # vllm  vllm-ascend
 
 # Use mirror to speed up download
-# docker pull quay.nju.edu.cn/ascend/cann:|cann_image_tag|
+# docker pull m.daocloud.io/quay.io/ascend/cann:|cann_image_tag|
 export IMAGE=quay.io/ascend/cann:|cann_image_tag|
 docker run --rm --name vllm-ascend-ut \
     -v $(pwd):/vllm-project \

docs/source/developer_guide/performance_and_debug/optimization_and_tuning.md

@@ -55,7 +55,7 @@ pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple
 pip install modelscope pandas datasets gevent sacrebleu rouge_score pybind11 pytest
 
 # Configure this var to speed up model download
-VLLM_USE_MODELSCOPE=true
+export VLLM_USE_MODELSCOPE=True
 ```
 
 Please follow the [Installation Guide](https://docs.vllm.ai/projects/ascend/en/latest/installation.html) to make sure vLLM and vllm-ascend are installed correctly.
@@ -85,7 +85,7 @@ wget https://repo.oepkgs.net/ascend/pytorch/vllm/python/py311_bisheng.tar.gz
 
 # Configure python and pip
 cp ./*.so* /usr/local/lib
-tar -zxvf ./py311_bisheng.*  -C /usr/local/
+tar -zxvf ./py311_bisheng.tar.gz -C /usr/local/
 mv  /usr/local/py311_bisheng/  /usr/local/python
 sed -i "1c#\!/usr/local/python/bin/python3.11" /usr/local/python/bin/pip3
 sed -i "1c#\!/usr/local/python/bin/python3.11" /usr/local/python/bin/pip3.11

docs/source/developer_guide/performance_and_debug/performance_benchmark.md

@@ -159,7 +159,7 @@ vllm bench throughput \
 If successful, you will see the following output
 
 ```shell
-Processed prompts: 100%|█| 10/10 [00:03<00:00,  2.74it/s, est. speed input: 351.02 toks/s, output: 351.02 toks/s
+Processed prompts: 100%|█| 10/10 [00:03<00:00,  2.74it/s, est. speed input: 351.02 toks/s, output: 351.02 toks/s]
 Throughput: 2.73 requests/s, 699.93 total tokens/s, 349.97 output tokens/s
 Total num prompt tokens:  1280
 Total num output tokens:  1280