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

# Fine-Tuning Quick Start

> Train your first fine-tuned model with OpenPipe.

Fine-tuning open and closed models with custom hyperparameters only takes a few clicks.

<Note>
  <b>Before you begin:</b> Before training your first model, make sure you've [created a
  dataset](/features/datasets/quick-start) and imported at least 10 training entries.
</Note>

### Training a Model

<Steps title="Training a Model">
  <Step title="Navigate to Dataset">
    To train a model, navigate to the dataset you'd like to train your model on. Click the **Fine Tune** button in the top right corner of the **General** tab.

    <Frame>
      <img src="https://mintcdn.com/openpipe/yLyh_RHELnvU-7tP/images/features/fine-tuning/fine-tune-modal.png?fit=max&auto=format&n=yLyh_RHELnvU-7tP&q=85&s=7112995435a05cd45d5caa3cf4d4fc27" alt="" width="2992" height="1716" data-path="images/features/fine-tuning/fine-tune-modal.png" />
    </Frame>
  </Step>

  <Step title="Name your Model">
    Choose a descriptive name for your new model. This name will be used as the `model` parameter when querying it in code.
    You can always rename your model later.
  </Step>

  <Step title="Select Base Model">
    Select the base model you'd like to fine-tune on. We recommend starting with Llama 3.1 8B if you aren't sure which to choose.

    <Frame>
      <img src="https://mintcdn.com/openpipe/ODS5wc6pSZpoOUK8/images/features/fine-tuning/select-base-model.png?fit=max&auto=format&n=ODS5wc6pSZpoOUK8&q=85&s=80eb7cef3c6c218373836ef831ff0a30" alt="" width="1194" height="836" data-path="images/features/fine-tuning/select-base-model.png" />
    </Frame>
  </Step>

  <Step title="Adjust Hyperparameters (optional)">
    Under **Advanced Options**, you can optionally adjust the hyperparameters to fine-tune your model.
    You can leave these at their default values if you aren't sure which to choose.

    <Frame>
      <img src="https://mintcdn.com/openpipe/yLyh_RHELnvU-7tP/images/features/fine-tuning/adjust-hyperparameters.png?fit=max&auto=format&n=yLyh_RHELnvU-7tP&q=85&s=a06f709ecb484ff4f7d9d5b894235683" alt="" width="1190" height="792" data-path="images/features/fine-tuning/adjust-hyperparameters.png" />
    </Frame>
  </Step>

  <Step title="Start Training">
    Click **Start Training** to begin the training process.
    The training job may take a few minutes or a few hours to complete, depending on the amount of training data, the base model, and the hyperparameters you choose.

    <Frame>
      <img src="https://mintcdn.com/openpipe/ODS5wc6pSZpoOUK8/images/features/fine-tuning/trained-model.png?fit=max&auto=format&n=ODS5wc6pSZpoOUK8&q=85&s=c60717ba01b642bc1a36140572dcd31f" alt="" width="2998" height="1718" data-path="images/features/fine-tuning/trained-model.png" />
    </Frame>
  </Step>
</Steps>

To learn more about fine-tuning through the webapp, check out the [Fine-Tuning via Webapp](/features/fine-tuning/overview) page.
To learn about fine-tuning via API, see our [Fine Tuning via API](/api-reference/fine-tuning) page.