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 15, 13:30 UTC
[Docs] Fix a link and grammar issue in production-stack.md (#16809)
Signed-off-by: windsonsea <haifeng.yao@daocloud.io>
Michael Yao committed
Apr 18, 2025 at 14:42 UTC
26507f8973e834dce56abb0796c1d5e833b08a31
1 file changed
+1
-1
docs/source/deployment/integrations/production-stack.md
+1
-1
@@ -16,7 +16,7 @@ Ensure that you have a running Kubernetes environment with GPU (you can follow [
16
17
## Deployment using vLLM production stack
18
19
-The standard vLLM production stack install uses a Helm chart. You can run this [bash script](https://github.com/vllm-project/production-stack/blob/main/tutorials/install-helm.sh) to install Helm on your GPU server.
19
+The standard vLLM production stack is installed using a Helm chart. You can run this [bash script](https://github.com/vllm-project/production-stack/blob/main/utils/install-helm.sh) to install Helm on your GPU server.
20
21
To install the vLLM production stack, run the following commands on your desktop:
22