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[Doc][Misc] Comprehensive documentation cleanup and grammatical fixes (#8073)

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What this PR does / why we need it?
This pull request performs a comprehensive cleanup of the vLLM Ascend
documentation. It fixes numerous typos, grammatical errors, and phrasing
issues across community guidelines, developer documents, hardware
tutorials, and feature guides. Key improvements include correcting
hardware names (e.g., Atlas 300I), fixing broken links, cleaning up code
examples (removing duplicate flags and trailing commas), and improving
the clarity of technical explanations. These changes are necessary to
ensure the documentation is professional, accurate, and easy for users
to follow.

Does this PR introduce any user-facing change?
No, this PR contains documentation-only updates.

How was this patch tested?
The changes were manually reviewed for accuracy and grammatical
correctness. No functional code changes were introduced.

---------

Signed-off-by: herizhen <1270637059@qq.com>
Signed-off-by: herizhen <59841270+herizhen@users.noreply.github.com>
This commit is contained in:
herizhen
2026-04-09 15:37:57 +08:00
committed by GitHub
parent c40a387f63
commit 0d1424d81a
71 changed files with 1295 additions and 1296 deletions
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96
docs/source/developer_guide/evaluation/using_ais_bench.md
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@@ -81,74 +81,74 @@ You can choose one or multiple datasets to execute accuracy evaluation.
1. `C-Eval` dataset.
Take `C-Eval` dataset as an example. You can refer to [Datasets](https://gitee.com/aisbench/benchmark/tree/master/ais_bench/benchmark/configs/datasets) for more datasets. Each dataset has a `README.md` with detailed download and installation instructions.
Take `C-Eval` dataset as an example. You can refer to [Datasets](https://gitee.com/aisbench/benchmark/tree/master/ais_bench/benchmark/configs/datasets) for more datasets. Each dataset has a `README.md` with detailed download and installation instructions.
Download dataset and install it to specific path.
Download dataset and install it to specific path.
```shell
cd ais_bench/datasets
mkdir ceval/
mkdir ceval/formal_ceval
cd ceval/formal_ceval
wget https://www.modelscope.cn/datasets/opencompass/ceval-exam/resolve/master/ceval-exam.zip
unzip ceval-exam.zip
rm ceval-exam.zip
```
```shell
cd ais_bench/datasets
mkdir ceval/
mkdir ceval/formal_ceval
cd ceval/formal_ceval
wget https://www.modelscope.cn/datasets/opencompass/ceval-exam/resolve/master/ceval-exam.zip
unzip ceval-exam.zip
rm ceval-exam.zip
```
2. `MMLU` dataset.
```shell
cd ais_bench/datasets
wget http://opencompass.oss-cn-shanghai.aliyuncs.com/datasets/data/mmlu.zip
unzip mmlu.zip
rm mmlu.zip
```
```shell
cd ais_bench/datasets
wget http://opencompass.oss-cn-shanghai.aliyuncs.com/datasets/data/mmlu.zip
unzip mmlu.zip
rm mmlu.zip
```
3. `GPQA` dataset.
```shell
cd ais_bench/datasets
wget http://opencompass.oss-cn-shanghai.aliyuncs.com/datasets/data/gpqa.zip
unzip gpqa.zip
rm gpqa.zip
```
```shell
cd ais_bench/datasets
wget http://opencompass.oss-cn-shanghai.aliyuncs.com/datasets/data/gpqa.zip
unzip gpqa.zip
rm gpqa.zip
```
4. `MATH` dataset.
```shell
cd ais_bench/datasets
wget http://opencompass.oss-cn-shanghai.aliyuncs.com/datasets/data/math.zip
unzip math.zip
rm math.zip
```
```shell
cd ais_bench/datasets
wget http://opencompass.oss-cn-shanghai.aliyuncs.com/datasets/data/math.zip
unzip math.zip
rm math.zip
```
5. `LiveCodeBench` dataset.
```shell
cd ais_bench/datasets
git lfs install
git clone https://huggingface.co/datasets/livecodebench/code_generation_lite
```
```shell
cd ais_bench/datasets
git lfs install
git clone https://huggingface.co/datasets/livecodebench/code_generation_lite
```
6. `AIME 2024` dataset.
```shell
cd ais_bench/datasets
mkdir aime/
cd aime/
wget http://opencompass.oss-cn-shanghai.aliyuncs.com/datasets/data/aime.zip
unzip aime.zip
rm aime.zip
```
```shell
cd ais_bench/datasets
mkdir aime/
cd aime/
wget http://opencompass.oss-cn-shanghai.aliyuncs.com/datasets/data/aime.zip
unzip aime.zip
rm aime.zip
```
7. `GSM8K` dataset.
```shell
cd ais_bench/datasets
wget http://opencompass.oss-cn-shanghai.aliyuncs.com/datasets/data/gsm8k.zip
unzip gsm8k.zip
rm gsm8k.zip
```
```shell
cd ais_bench/datasets
wget http://opencompass.oss-cn-shanghai.aliyuncs.com/datasets/data/gsm8k.zip
unzip gsm8k.zip
rm gsm8k.zip
```
#### Configuration

2
docs/source/developer_guide/evaluation/using_evalscope.md
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@@ -87,7 +87,7 @@ After 1 to 2 minutes, the output is shown below:
+---------------------+-----------+-----------------+----------+-------+---------+---------+
```
See more detail in [EvalScope doc - Model API Service Evaluation](https://evalscope.readthedocs.io/en/latest/get_started/basic_usage.html#model-api-service-evaluation).
See more details in [EvalScope doc - Model API Service Evaluation](https://evalscope.readthedocs.io/en/latest/get_started/basic_usage.html#model-api-service-evaluation).
## 4. Run model inference stress testing using EvalScope

2
docs/source/developer_guide/evaluation/using_lm_eval.md
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@@ -214,7 +214,7 @@ Tasks|Version| Filter |n-shot| Metric | |Value | |Stderr|
## Use Offline Datasets
Take GSM8K (single dataset) and MMLU (multi-subject dataset) as examples, and you can see more from [here][2].
Take GSM8K (single dataset) and MMLU (multi-subject dataset) as examples, and you can see more from [using-local-datasets][2].
```bash
# set HF_DATASETS_OFFLINE when using offline datasets

4
docs/source/developer_guide/evaluation/using_opencompass.md
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@@ -4,7 +4,7 @@ This document guides you to conduct accuracy testing using [OpenCompass](https:/
## 1. Online Server
You can run docker container to start the vLLM server on a single NPU:
You can run a docker container to start the vLLM server on a single NPU:
```{code-block} bash
:substitutions:
@@ -116,7 +116,7 @@ python3 run.py opencompass/configs/eval_vllm_ascend_demo.py --debug
After 1 to 2 minutes, the output is shown below:
```shell
The markdown format results is as below:
The markdown format results are as below:
| dataset | version | metric | mode | Qwen2.5-7B-Instruct-vLLM-API |
|----- | ----- | ----- | ----- | -----|