llama-stack-mirror/llama_stack/templates/sambanova/doc_template.md
2024-11-29 17:26:58 -06:00

1.7 KiB

Sambanova Distribution

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self

The llamastack/distribution-{{ name }} distribution consists of the following provider configurations.

{{ providers_table }}

{% if run_config_env_vars %}

Environment Variables

The following environment variables can be configured:

{% for var, (default_value, description) in run_config_env_vars.items() %}

  • {{ var }}: {{ description }} (default: {{ default_value }}) {% endfor %} {% endif %}

{% if default_models %}

Models

The following models are available by default:

{% for model in default_models %}

  • {{ model.model_id }} ({{ model.provider_model_id }}) {% endfor %} {% endif %}

Prerequisite: API Keys

Make sure you have access to a Sambanova API Key. You can get one by visiting Sambanova.

Running Llama Stack with Sambanova

You can do this via Conda (build code) or Docker which has a pre-built image.

Available INFERENCE_MODEL

  • Meta-Llama-3.1-8B-Instruct
  • Meta-Llama-3.1-70B-Instruct
  • Meta-Llama-3.1-405B-Instruct
  • Meta-Llama-3.2-1B-Instruct
  • Meta-Llama-3.2-3B-Instruct

Via Docker

This method allows you to get started quickly without having to build the distribution code.

LLAMA_STACK_PORT=5001
docker run \
  -it \
  -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
  llamastack/distribution-{{ name }} \
  --port $LLAMA_STACK_PORT \
  --env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY \
  --env INFERENCE_MODEL=$INFERENCE_MODEL

Via Conda

llama stack build --template sambanova --image-type conda
llama stack run ./run.yaml \
  --port $LLAMA_STACK_PORT \
  --env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY \
  --env INFERENCE_MODEL=$INFERENCE_MODEL