[Doc] Upgrade multi-node doc (#4365)

### What this PR does / why we need it?
When we are using `Ascend scheduler`, the param `max_num_batched_tokens`
should be larger than `max_model_len`, otherwise, will encountered the
follow error:
```shell
Value error, Ascend scheduler is enabled without chunked prefill feature. Argument max_num_batched_tokens (4096) is smaller than max_model_len (32768). This effectively limits the maximum sequence length to max_num_batched_tokens and makes vLLM reject longer sequences. Please increase max_num_batched_tokens or decrease max_model_len. [type=value_error, input_value=ArgsKwargs((), {'model_co...g': {'enabled': True}}}), input_type=ArgsKwargs]
```

### Does this PR introduce _any_ user-facing change?
Users/Developers who running the model according to the
[tutorial](https://docs.vllm.ai/projects/ascend/en/latest/tutorials/multi_node.html),
the parameters can be specified correctly.

### How was this patch tested?

- vLLM version: v0.11.0
- vLLM main:
2918c1b49c

---------

Signed-off-by: wangli <wangli858794774@gmail.com>

.github/workflows/_e2e_nightly_multi_node.yaml

@@ -216,7 +216,7 @@ jobs:
 
               # 1) check follower pods
               ALL_FOLLOWERS_READY=true
-              for ((i=1; i<${SIZE}; i++)); do
+              for ((i=1; i<SIZE; i++)); do
                 POD="${POD_PREFIX}-${i}"
                 PHASE=$(kubectl get pod "$POD" -n "$NAMESPACE" -o jsonpath='{.status.phase}' 2>/dev/null || echo "NotFound")
                 READY=$(kubectl get pod "$POD" -n "$NAMESPACE" -o jsonpath='{.status.containerStatuses[*].ready}' 2>/dev/null)

docs/source/tutorials/multi_node.md

@@ -131,9 +131,9 @@ vllm serve vllm-ascend/DeepSeek-V3.1-W8A8 \
 --served-model-name deepseek_v3.1 \
 --enable-expert-parallel \
 --max-num-seqs 16 \
---max-model-len 32768 \
+--max-model-len 8192 \
 --quantization ascend \
---max-num-batched-tokens 4096 \
+--max-num-batched-tokens 8192 \
 --trust-remote-code \
 --no-enable-prefix-caching \
 --gpu-memory-utilization 0.9 \
@@ -176,8 +176,8 @@ vllm serve vllm-ascend/DeepSeek-V3.1-W8A8 \
 --quantization ascend \
 --served-model-name deepseek_v3.1 \
 --max-num-seqs 16 \
---max-model-len 32768 \
+--max-model-len 8192 \
---max-num-batched-tokens 4096 \
+--max-num-batched-tokens 8192 \
 --enable-expert-parallel \
 --trust-remote-code \
 --no-enable-prefix-caching \

docs/source/tutorials/multi_node_kimi.md

@@ -88,8 +88,8 @@ vllm serve /home/cache/weights/Kimi-K2-Instruct-W8A8 \
 --tensor-parallel-size 8 \
 --enable-expert-parallel \
 --max-num-seqs 16 \
---max-model-len 32768 \
+--max-model-len 8192 \
---max-num-batched-tokens 4096 \
+--max-num-batched-tokens 8192 \
 --trust-remote-code \
 --no-enable-prefix-caching \
 --gpu-memory-utilization 0.9 \
@@ -130,9 +130,9 @@ vllm serve /home/cache/weights/Kimi-K2-Instruct-W8A8 \
 --tensor-parallel-size 8 \
 --served-model-name kimi \
 --max-num-seqs 16 \
---max-model-len 32768 \
+--max-model-len 8192 \
 --quantization ascend \
---max-num-batched-tokens 4096 \
+--max-num-batched-tokens 8192 \
 --enable-expert-parallel \
 --trust-remote-code \
 --no-enable-prefix-caching \