> ## 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.

# Training sets

> The dataset used to fine-tune the Luna base model during a run.

A **training set** is the dataset that fine-tunes your [Luna base model](/luna-studio/ui/core-concepts#base-models) during a [training run](/luna-studio/ui/runs/lifecycle). Training sets are typically much larger than test sets.

## Sources

In the run creation flow, you choose one of three top-level paths:

<CardGroup cols={3}>
  <Card title="Generate from test set" icon="wand-magic-sparkles">
    Luna Studio uses 20% of your test set as seeds and synthetically generates training data.
  </Card>

  <Card title="Add unlabelled training logs" icon="upload">
    Upload or import production logs. Luna Studio labels unlabelled logs before training.
  </Card>

  <Card title="Use existing training set" icon="database">
    Reuse a generated, labelled, or uploaded training dataset from your workspace.
  </Card>
</CardGroup>

The **Add training logs** path lets you upload a `.csv` or `.jsonl` file, fetch a file from URL, or import a dataset from Galileo. Those same import methods are also available from the [Datasets page](/luna-studio/ui/datasets/overview) **Add training set** button.

## Required schema

Check the [pre-requisites](/luna-studio/ui/prerequisites#required-dataset-format) section for details

### Labelled vs. unlabelled

When you add training logs, Luna Studio validates whether the dataset already has labels:

If labels are missing, Luna Studio will automatically label the data using your LLM-as-judge prompt before training the model.

## Generated training sets

The most common path for a first run is **Generate from test set**. The flow:

1. Luna Studio uses 20% of your test set as seed examples.
2. We first synthetically generate a sample training set for review.
3. You review the sample rows and optionally regenerate with feedback.
4. Luna Studio generates the full training set.

See [Step 3 — Training set](/luna-studio/ui/runs/new-run/step-3-training-set#generate-from-test-set) for the full reference.

The resulting dataset shows up on the [Datasets page](/luna-studio/ui/datasets/overview) with source **Generated** and a subtitle like "Generated from rag-eval-v2".

## File formats

For uploads and URL fetches:

* **CSV** — standard comma-separated. Headers required.
* **JSONL** — one JSON object per line, with `input` and (optionally) `label` keys.

## Where to go next

<CardGroup cols={2}>
  <Card title="Generate from test set" icon="wand-magic-sparkles" href="/luna-studio/ui/runs/new-run/step-3-training-set">
    The most common path for first runs.
  </Card>

  <Card title="Add a dataset" icon="upload" href="/luna-studio/ui/datasets/add-a-dataset">
    Walk through the Upload / URL / Galileo flows.
  </Card>

  <Card title="Test sets" icon="database" href="/luna-studio/ui/datasets/test-sets">
    The other dataset type — used to evaluate the metric.
  </Card>

  <Card title="Validation" icon="circle-check" href="/luna-studio/ui/datasets/validation">
    Schema and content checks Luna runs.
  </Card>
</CardGroup>