List Customization Configs#

Get a list of available customization configurations and their details to determine which models are available for fine-tuning.

Tip

These configs are typically added by your cluster administrator during the initial setup of NeMo Customizer.

Prerequisites#

Before you can get a list of customization configurations, make sure that you have:

  • Access to the NeMo Customizer service

Options#

API#

  1. Submit a GET request to /v1/customization/configs.

    BASE_MODEL="meta/llama-3.1-8b-instruct"
TRAINING_TYPE="sft"
FINETUNING_TYPE="lora"

curl --get \
  "${CUSTOMIZER_SERVICE_URL}/v1/customization/configs" \
  --data-urlencode "page=1" \
  --data-urlencode "page_size=10" \
  --data-urlencode "sort=-created_at" \
  --data-urlencode "filter[base_model]=${BASE_MODEL}" \
  --data-urlencode "filter[training_type]=${TRAINING_TYPE}" \
  --data-urlencode "filter[finetuning_type]=${FINETUNING_TYPE}" \
  --data-urlencode "filter[enabled]=true" | jq

    You can use either use the full {namespace}/{name} fields of a returned config object, or just use name (which would use the default namespace), and set the config parameter when creating a customization job.

  2. Review the returned customization configs.

    Example Response
    {
    "object": "list",
    "data": [
        {
            "created_at": "2024-11-26T02:58:55.339737",
            "updated_at": "2024-11-26T02:58:55.339737",
            "id": "customization_config-MedVscVbr4pgLhLgKTLbv9",
            "name": "lama-3.1-8b-instruct@v1.0.0+A100",
            "namespace": "default",
            "description": "Configuration for training LLama 3.1 8B on A100 GPUs",
            "target": "meta/llama-3.1-8b-instruct@2.0",
            "training_options": [
                {
                    "training_type": "sft",
                    "finetuning_type": "lora",
                    "num_gpus": 2,
                    "num_nodes": 1,
                    "tensor_parallel_size": 1,
                    "micro_batch_size": 1,
                },
            ],
            "training_precision": "bf16",
            "max_seq_length": 2048,
            "pod_spec": "{ object }",
            "prompt_template": "string",
            "chat_prompt_template": "string",
            "dataset_schemas": "{ object }",
            "project": "string",
            "ownership": "{ object }"
        },
    ],
    "pagination": {
        "page": 1,
        "page_size": 10,
        "current_page_size": 2,
        "total_pages": 1,
        "total_results": 2
    },
    "sort": "-created_at"
}

    Tip

    The num_gpus multiplied by the num_nodes is the total number of GPUs required to run a fine tuning.

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