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### What this PR does / why we need it?
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---------
Signed-off-by: 李少鹏 <lishaopeng21@huawei.com>
### What this PR does / why we need it?
This PR improves the readability of the documentation by fixing typos,
correcting command extensions, and fixing broken links in the Chinese
README.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Documentation changes only.
---------
Signed-off-by: sunshine202600 <sunshine202600@163.com>
### What this PR does / why we need it?
Main updates include:
- update model IDs and default model paths in serving / offline
inference examples
- adjust some command snippets and notes for better copy-paste usability
- replace `SamplingParams` argument usage from `max_completion_tokens`
to `max_tokens`（**Offline** inference currently **does not support** the
"max_completion_tokens"）
``` bash
Traceback (most recent call last):
File "/vllm-workspace/vllm-ascend/qwen-next.py", line 18, in <module>
sampling_params = SamplingParams(temperature=0.6, top_p=0.95, top_k=40, max_completion_tokens=32)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: Unexpected keyword argument 'max_completion_tokens'
[ERROR] 2026-03-17-09:57:40 (PID:276, Device:-1, RankID:-1) ERR99999 UNKNOWN applicaiton exception
```
- refresh **Qwen3-Omni-30B-A3B-Thinking** recommended environment
variable
``` bash
export HCCL_BUFFSIZE=512
export HCCL_OP_EXPANSION_MODE=AIV
```
``` bash
EZ9999[PID: 25038] 2026-03-17-08:21:12.001.372 (EZ9999): HCCL_BUFFSIZE is too SMALL, maxBs = 256, h = 2048,
epWorldSize = 2, localMoeExpertNum = 64, sharedExpertNum = 0, tokenNeedSizeDispatch = 4608, tokenNeedSizeCombine
= 4096, k = 8, NEEDED_HCCL_BUFFSIZE(((maxBs * tokenNeedSizeDispatch * ep_worldsize * localMoeExpertNum) +
(maxBs * tokenNeedSizeCombine * (k + sharedExpertNum))) * 2) = 305MB, HCCL_BUFFSIZE=200MB.
[FUNC:CheckWinSize][FILE:moe_distribute_dispatch_v2_tiling.cpp][LINE:984]
```
- fix **Qwen3-reranker** example usage to match the current **pooling
runner** interface and score output access
``` python
model = LLM(
model=model_name,
task="score", # need fix
hf_overrides={
"architectures": ["Qwen3ForSequenceClassification"],
"classifier_from_token": ["no", "yes"],
```
--->
``` python
model = LLM(
model=model_name,
runner="pooling",
hf_overrides={
"architectures": ["Qwen3ForSequenceClassification"],
"classifier_from_token": ["no", "yes"],
```
- modify **PaddleOCR-VL** parameter `TASK_QUEUE_ENABLE` from `2` to `1`
``` bash
(EngineCore_DP0 pid=26273) RuntimeError: NPUModelRunner init failed, error is NPUModelRunner failed, error
is Do not support TASK_QUEUE_ENABLE = 2 during NPU graph capture, please export TASK_QUEUE_ENABLE=1/0.
```
These changes are needed because several documentation examples had
drifted from the current runtime behavior and recommended invocation
patterns, which could confuse users when following the tutorials
directly.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
- vLLM version: v0.17.0
- vLLM main:
4497431df6
Signed-off-by: MrZ20 <2609716663@qq.com>
### What this PR does / why we need it?
Upload doc for qwen3.5-27B and qwen3.5-397B-A17B on Ascend
Base on vllm-ascend:v0.17.0rc1
- vLLM version: v0.17.0
- vLLM main:
4034c3d32e
---------
Signed-off-by: pppeng <zepengliu912@qq.com>
Signed-off-by: pppeng <60355449+ppppeng@users.noreply.github.com>
