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Deployment LLM with Deka GPU + NIM

Download Helm Chart

After you have fulfilled the prerequisites above, the next step is to download Helm Chart by executing the following syntax.

helm fetch https://helm.ngc.nvidia.com/nim/charts/nim-llm-1.3.0.tgz --username=\$oauthtoken --password=<your token> 

After successfully downloading Helm Chart, the next step is to extract the file by executing the following syntax.

tar -xvzf nim-llm-1.3.0.tgz 

Enter the extracted folder by running the syntax below.

cd nim-llm

Change the security context in the values.yaml file

Determine the base model used, in this guide using meta llama 8b.

Add link model

Edit the gpu based on the needs.

Put your api key in line "ngcAPI Key".

Edit the storage based on the needs.

Edit Storage

Save the file after updating, press CTRL + O to save, and CTRL + X to exit.

Add Runtime NVIDIA

Open the deployment.yaml file in the files folder by executing the following syntax.

nano files/deployment.yaml

After the deployment.yaml file opens, look for the specsection and add runtimeClassName: nvidia according to the image below.

Add runtimeClassName

Save the file after updating, press CTRL + O to save, and CTRL + X to exit.

Install Helm Chart

Install Helm Chart by executing the following syntax.

helm install nim . -f values.yaml 
Install Helm Chart

Wait until the installation process is complete and run the following syntax to see the list of available pods.

kubectl get pods

Testing

When finished, run the following syntax to display a list of nim services in the namespace.

kubectl get svc -n nim

In the image above, you can see nim-llm using the IP cluster 10.250.225.0 and the status is active. Run the following syntax to log into a container running inside a pod in Kubernetes.

kubectl exec -it multitoll -- bash
Testing

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