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A high-throughput and memory-efficient inference and serving engine for LLMs

Mirrored from https://github.com/tduncan-lum/Nvidia-Optimization-Stack---VLLM.git

Synced Nov 14, 05:30 UTC

[docs] standardize Hugging Face env var to `HF_TOKEN` (deprecates `HUGGING_FACE_HUB_TOKEN`) (#27020)

Signed-off-by: Kay Yan <kay.yan@daocloud.io>

Kay Yan committed Oct 16, 2025 at 22:31 UTC 02d709a6f1e442ab8f1129170eac338a6b3a4b1f
3 files changed +8 -8
docs/deployment/docker.md
+3 -3
@@ -10,7 +10,7 @@ The image can be used to run OpenAI compatible server and is available on Docker
10 ```bash
11 docker run --runtime nvidia --gpus all \
12 -v ~/.cache/huggingface:/root/.cache/huggingface \
13 - --env "HUGGING_FACE_HUB_TOKEN=$HF_TOKEN" \
13 + --env "HF_TOKEN=$HF_TOKEN" \
14 -p 8000:8000 \
15 --ipc=host \
16 vllm/vllm-openai:latest \
@@ -22,7 +22,7 @@ This image can also be used with other container engines such as [Podman](https:
22 ```bash
23 podman run --device nvidia.com/gpu=all \
24 -v ~/.cache/huggingface:/root/.cache/huggingface \
25 - --env "HUGGING_FACE_HUB_TOKEN=$HF_TOKEN" \
25 + --env "HF_TOKEN=$HF_TOKEN" \
26 -p 8000:8000 \
27 --ipc=host \
28 docker.io/vllm/vllm-openai:latest \
@@ -128,7 +128,7 @@ To run vLLM with the custom-built Docker image:
128 docker run --runtime nvidia --gpus all \
129 -v ~/.cache/huggingface:/root/.cache/huggingface \
130 -p 8000:8000 \
131 - --env "HUGGING_FACE_HUB_TOKEN=<secret>" \
131 + --env "HF_TOKEN=<secret>" \
132 vllm/vllm-openai <args...>
133 ```
134
docs/deployment/frameworks/lws.md
+2 -2
@@ -35,7 +35,7 @@ Deploy the following yaml file `lws.yaml`
35 - name: vllm-leader
36 image: docker.io/vllm/vllm-openai:latest
37 env:
38 - - name: HUGGING_FACE_HUB_TOKEN
38 + - name: HF_TOKEN
39 value: <your-hf-token>
40 command:
41 - sh
@@ -83,7 +83,7 @@ Deploy the following yaml file `lws.yaml`
83 ephemeral-storage: 800Gi
84 cpu: 125
85 env:
86 - - name: HUGGING_FACE_HUB_TOKEN
86 + - name: HF_TOKEN
87 value: <your-hf-token>
88 volumeMounts:
89 - mountPath: /dev/shm
docs/deployment/k8s.md
+3 -3
@@ -82,7 +82,7 @@ Next, start the vLLM server as a Kubernetes Deployment and Service:
82 "vllm serve meta-llama/Llama-3.2-1B-Instruct"
83 ]
84 env:
85 - - name: HUGGING_FACE_HUB_TOKEN
85 + - name: HF_TOKEN
86 valueFrom:
87 secretKeyRef:
88 name: hf-token-secret
@@ -209,7 +209,7 @@ INFO: Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)
209 "vllm serve mistralai/Mistral-7B-Instruct-v0.3 --trust-remote-code --enable-chunked-prefill --max_num_batched_tokens 1024"
210 ]
211 env:
212 - - name: HUGGING_FACE_HUB_TOKEN
212 + - name: HF_TOKEN
213 valueFrom:
214 secretKeyRef:
215 name: hf-token-secret
@@ -298,7 +298,7 @@ INFO: Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)
298 "vllm serve mistralai/Mistral-7B-v0.3 --port 8000 --trust-remote-code --enable-chunked-prefill --max_num_batched_tokens 1024"
299 ]
300 env:
301 - - name: HUGGING_FACE_HUB_TOKEN
301 + - name: HF_TOKEN
302 valueFrom:
303 secretKeyRef:
304 name: hf-token-secret