> ## Documentation Index
> Fetch the complete documentation index at: https://docs.galileo.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Run Labelling only

> Label an existing training dataset using your metric definition.

## When to use this flow

Use labelling-only mode when you already have training examples, but they are not labelled for the metric you want to train.

This flow uses your LLM-as-a-Judge prompt to label the dataset you already have. It does not generate new synthetic examples.

## What changes in the config

To enable this flow, set:

* `labelling.label_only_mode: true`
* `metric.llmaj_source_prompt` to the prompt used for judging / labeling

If you are using Huggingface input, your dataset should contain a `train` split

If you are using CSV input, you must also set:

* `source_data.dataset.csv.train_file_path`

## Minimal example

```yaml theme={null}
data_generation:
  metric:
    llmaj_source_prompt: |
      ...
  source_data:
    dataset:
      source_type: "csv"
      csv:
        file_path: "./test.csv"
        train_file_path: "./train.csv"
      columns:
        features: ["input"]
        label: "label"
  labelling:
    enabled: false
    label_only_mode: true
```

## What happens next

After labeling completes, continue to the training step using the labeled dataset.

Next: [Training overview](/luna-studio/sdk/how-to-train-your-luna-metric/training/overview)