README.md

AI Singapore SEA-LION model served by vLLM inference server with Docker Compose

Requirements

• Docker
• GPU: compute capability 7.0 or higher (e.g., V100, T4, RTX20xx, A100, L4, H100, etc.)
• CUDA 12.1
• Check https://docs.vllm.ai/en/latest/getting_started/installation.html#requirements for the up to date requirements
• 80GB of disk storage for the model and docker image

SEA-LION

This section describes the setup of the SEA-LION models.

SEA-LION v2.1

• Download LLaMA3 8B CPT SEA-LIONv2.1 Instruct.
• Copy the model or add a symbolic link in the models directory. The path is ./models/llama3-8b-cpt-sea-lionv2.1-instruct. For example, if the model was downloaded to ~/downloads/llama3-8b-cpt-sea-lionv2.1-instruct, the symbolic link is added by:

  ln -s ~/downloads/llama3-8b-cpt-sea-lionv2.1-instruct models/

SEA-LION v3

• Download Gemma2 9B CPT SEA-LIONv3 Instruct.
• Copy the model or add a symbolic link in the models directory. The path is ./models/gemma2-9b-cpt-sea-lionv3-instruct. For example, if the model was downloaded to ~/downloads/gemma2-9b-cpt-sea-lionv3-instruct, the symbolic link is added by:

  ln -s ~/downloads/gemma2-9b-cpt-sea-lionv3-instruct models/

• Set MODEL_NAME.

   export MODEL_NAME=gemma2-9b-cpt-sea-lionv3-instruct

Start vLLM

• Start the service.

  docker compose up

• vLLM is deployed as a server that implements the OpenAI API protocol. By default, it starts the server at http://localhost:8000. This server can be queried in the same format as OpenAI API. For example, list the models:

  curl http://localhost:8000/v1/models

• Test the service. Update the model name accordingly.

  curl http://localhost:8000/v1/completions \
    -H "Content-Type: application/json" \
    -d '{
        "model": "llama3-8b-cpt-sea-lionv2.1-instruct",
        "prompt": "Artificial Intelligence is",
        "max_tokens": 20,
        "temperature": 0.8,
        "repetition_penalty": 1.2
    }'

Customisation

• To use another model:
  • Download the model to the models directory.
  • Update the $MODEL_NAME environment variable. For example, if the model is downloaded to ./models/foo-model-30b:

    export MODEL_NAME=foo-model-30b