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[Docs] Update server entrypoint examples (#42077)

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Signed-off-by: Ethan Feng <ethan.fengch@gmail.com>
This commit is contained in:
Ethan Feng
2026-05-09 02:03:52 +00:00
committed by GitHub
parent 236bf9d152
commit a43bc34baf
4 changed files with 5 additions and 8 deletions
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docs/deployment/frameworks/runpod.md
+1 -2
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@@ -12,8 +12,7 @@ vLLM can be deployed on [RunPod](https://www.runpod.io/), a cloud GPU platform t
SSH into your RunPod pod and launch the vLLM OpenAI-compatible server:
```bash
python -m vllm.entrypoints.openai.api_server \
--model <model-name> \
vllm serve <model-name> \
--host 0.0.0.0 \
--port 8000
```
docs/deployment/integrations/kthena.md
+2 -3
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@@ -79,9 +79,8 @@ Key points from the example YAML:
- -c
- >
bash /vllm-workspace/examples/ray_serving/multi-node-serving.sh leader --ray_cluster_size=2;
python3 -m vllm.entrypoints.openai.api_server
vllm serve meta-llama/Llama-3.1-405B-Instruct
--port 8080
--model meta-llama/Llama-3.1-405B-Instruct
--tensor-parallel-size 8
--pipeline-parallel-size 2
```
@@ -145,7 +144,7 @@ spec:
- sh
- -c
- "bash /vllm-workspace/examples/ray_serving/multi-node-serving.sh leader --ray_cluster_size=2;
python3 -m vllm.entrypoints.openai.api_server --port 8080 --model meta-llama/Llama-3.1-405B-Instruct --tensor-parallel-size 8 --pipeline-parallel-size 2"
vllm serve meta-llama/Llama-3.1-405B-Instruct --port 8080 --tensor-parallel-size 8 --pipeline-parallel-size 2"
resources:
limits:
nvidia.com/gpu: "8"