Chapter 5. Downloading a model from Hugging Face before running Red Hat AI Inference Server

Procedure

1. Open a shell prompt on the RHEL AI server.

2. Stop the Red Hat AI Inference Server service:

   [cloud-user@localhost ~]$ systemctl stop rhaiis

   Copy to Clipboard Toggle word wrap

3. Open a command prompt inside the Red Hat AI Inference Server container:

   [cloud-user@localhost ~]$ sudo podman run -it --rm \
     -e HF_TOKEN=<YOUR_HUGGING_FACE_HUB_TOKEN> \
     -v /var/lib/rhaiis/cache:/opt/app-root/src/.cache:Z \
     -v /var/lib/rhaiis/models:/opt/app-root/src/models:Z \
     --entrypoint /bin/bash \
     registry.redhat.io/rhaiis/model-opt-cuda-rhel9:3.2.3

   Copy to Clipboard Toggle word wrap
   Note

   You use the sudo command because the download writes to directories owned by the root group.

4. Inside the container, set HF_HUB_OFFLINE to 0. Run the following command:

   (app-root) /opt/app-root$ export HF_HUB_OFFLINE=0

   Copy to Clipboard Toggle word wrap

5. Download the model to the default directory. For example:

   (app-root) /opt/app-root$ hf download RedHatAI/granite-3.3-8b-instruct \
     --local-dir /opt/app-root/src/models/red-hat-ai-granite-3.3-8b-instruct \
     --token $HF_TOKEN

   Copy to Clipboard Toggle word wrap
   Note

   The rhaiis/vllm-cuda-rhel9 and rhaiis/model-opt-cuda-rhel9 containers both have the same version of the Hugging Face CLI available.

6. Exit the container:

   exit

   Copy to Clipboard Toggle word wrap

7. Edit the Red Hat AI Inference Server configuration file to use the downloaded model in offline mode:

   [cloud-user@localhost ~]$ sudo vi /etc/containers/systemd/rhaiis.container.d/install.conf

   Copy to Clipboard Toggle word wrap

   Update the configuration to enable offline mode and use the local model path:

   [Container]
   # Set to 1 to run in offline mode and disable model downloading at runtime
   Environment=HF_HUB_OFFLINE=1
   
   # Token is not required when running in offline mode with a local model
   # Environment=HUGGING_FACE_HUB_TOKEN=
   
   # Configure vLLM to use the locally downloaded model
   Exec=--model /opt/app-root/src/models/red-hat-ai-granite-3.3-8b-instruct \
        --tensor-parallel-size 1 \
        --served-model-name RedHatAI/granite-3.3-8b-instruct \
        --max-model-len 4096
   
   PublishPort=8000:8000
   ShmSize=4G
   
   [Install]
   WantedBy=multi-user.target

   Copy to Clipboard Toggle word wrap
   Note

   When you set the model location, you must set the location to the folder that is mapped inside the Red Hat AI Inference Server container, /opt/app-root/src/models/.

8. Reload the systemd configuration:

   [cloud-user@localhost ~]$ sudo systemctl daemon-reload

   Copy to Clipboard Toggle word wrap

9. Start the Red Hat AI Inference Server service:

   [cloud-user@localhost ~]$ sudo systemctl start rhaiis

   Copy to Clipboard Toggle word wrap

Verification

1. Monitor the service logs to verify the vLLM server is using the local model:

   [cloud-user@localhost ~]$ sudo podman logs -f rhaiis

   Copy to Clipboard Toggle word wrap

   Example output

   (APIServer pid=1) INFO 11-12 14:05:33 [utils.py:233] non-default args: {'model': '/opt/app-root/src/models/red-hat-ai-granite-3.3-8b-instruct', 'max_model_len': 4096, 'served_model_name': ['RedHatAI/granite-3.3-8b-instruct']}

   Copy to Clipboard Toggle word wrap

2. Test the inference server API:

   [cloud-user@localhost ~]$ curl -X POST -H "Content-Type: application/json" -d '{
       "prompt": "What is the capital of France?",
       "max_tokens": 50
   }' http://localhost:8000/v1/completions | jq

   Copy to Clipboard Toggle word wrap

   Example output

   {
     "id": "cmpl-f3e12cc62bee438c86af676332f8fe55",
     "object": "text_completion",
     "created": 1762956836,
     "model": "RedHatAI/granite-3.3-8b-instruct",
     "choices": [
       {
         "index": 0,
         "text": "\n\nThe capital of France is Paris.",
         "logprobs": null,
         "finish_reason": "stop",
         "stop_reason": null,
         "token_ids": null,
         "prompt_logprobs": null,
         "prompt_token_ids": null
       }
     ],
     "service_tier": null,
     "system_fingerprint": null,
     "usage": {
       "prompt_tokens": 7,
       "total_tokens": 18,
       "completion_tokens": 11,
       "prompt_tokens_details": null
     },
     "kv_transfer_params": null
   }

   Copy to Clipboard Toggle word wrap