[v0.11.0][Doc] Update doc (#3852)

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


Signed-off-by: hfadzxy <starmoon_zhang@163.com>
This commit is contained in:
zhangxinyuehfad
2025-10-29 11:32:12 +08:00
committed by GitHub
parent 6188450269
commit 75de3fa172
49 changed files with 724 additions and 701 deletions

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@@ -2,7 +2,7 @@
This document will guide you have model inference stress testing and accuracy testing using [EvalScope](https://github.com/modelscope/evalscope).
## 1. Online serving
## 1. Online server
You can run docker container to start the vLLM server on a single NPU:
@@ -31,7 +31,7 @@ docker run --rm \
vllm serve Qwen/Qwen2.5-7B-Instruct --max_model_len 26240
```
If your service start successfully, you can see the info shown below:
If the vLLM server is started successfully, you can see information shown below:
```
INFO: Started server process [6873]
@@ -39,7 +39,7 @@ INFO: Waiting for application startup.
INFO: Application startup complete.
```
Once your server is started, you can query the model with input prompts in new terminal:
Once your server is started, you can query the model with input prompts in a new terminal:
```
curl http://localhost:8000/v1/completions \
@@ -54,7 +54,7 @@ curl http://localhost:8000/v1/completions \
## 2. Install EvalScope using pip
You can install EvalScope by using:
You can install EvalScope as follows:
```bash
python3 -m venv .venv-evalscope
@@ -62,9 +62,9 @@ source .venv-evalscope/bin/activate
pip install gradio plotly evalscope
```
## 3. Run gsm8k accuracy test using EvalScope
## 3. Run GSM8K using EvalScope for accuracy testing
You can `evalscope eval` run gsm8k accuracy test:
You can use `evalscope eval` to run GSM8K for accuracy testing:
```
evalscope eval \
@@ -76,7 +76,7 @@ evalscope eval \
--limit 10
```
After 1-2 mins, the output is as shown below:
After 1 to 2 minutes, the output is shown below:
```shell
+---------------------+-----------+-----------------+----------+-------+---------+---------+
@@ -86,7 +86,7 @@ After 1-2 mins, the output is as 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 detail 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
@@ -98,7 +98,7 @@ pip install evalscope[perf] -U
### Basic usage
You can use `evalscope perf` run perf test:
You can use `evalscope perf` to run perf testing:
```
evalscope perf \
@@ -113,7 +113,7 @@ evalscope perf \
### Output results
After 1-2 mins, the output is as shown below:
After 1 to 2 minutes, the output is shown below:
```shell
Benchmarking summary:
@@ -172,4 +172,4 @@ Percentile results:
+------------+----------+---------+-------------+--------------+---------------+----------------------+
```
See more detail in: [EvalScope doc - Model Inference Stress Testing](https://evalscope.readthedocs.io/en/latest/user_guides/stress_test/quick_start.html#basic-usage).
See more detail in [EvalScope doc - Model Inference Stress Testing](https://evalscope.readthedocs.io/en/latest/user_guides/stress_test/quick_start.html#basic-usage).