> ## Documentation Index > Fetch the complete documentation index at: https://docs.gp.scale.com/llms.txt > Use this file to discover all available pages before exploring further. # Fine Tuning > Scale GP natively supports model fine tuning within the platform via the UI or API. ## Using the UI When navigating to the Models page, you can filter the listed models by the ones that are eligible for fine tuning. ### Fine-Tunable Models Fine-Tunable Models > ## > > Supported Models for Fine Tuning > > As of today (July 2024) we support only OpenAI models for fine tuning in Scale GP ### Training Datasets In order to be able to fine tune a model on the platform, you will need a training dataset. To create a new training dataset, navigate to "Training Datasets". A Training Dataset consists of a set of input and output pairs. Training Datasets Scale GP typically comes with a few pre-installed training datasets for typical tasks like RAG, Coding or Creative Writing. If you have a local installation of Scale GP without pre-installed training datasets, please contact Scale to get these datasets installed in your account. While each use case is different, a fine-tuning dataset should include at least include a **couple of hundred prompt response pairs** in order to have a meaningful impact on model performance for the respective domain. If you have a dataset of prompt response pairs ready to go, you can hit "New Dataset" and upload the dataset directly via the UI. Upload Dataset ### New Fine Tune After deciding for a training dataset, you can navigate back to "Models" and click "New Fine Tune" in the top right to being a fine tuning job. Subsequently, you can simply walk through the steps in the wizard to create the fine tune by picking the model type, base model to fine-tune, providing a name (and optionally description) and finally selecting a training dataset. New Fine Tune Step 1 New Fine Tune Step 2 ### Fine Tuning Jobs After completing the setup, you'll be able to monitor the status of the fine tuning job by navigating to "Fine-Tuning Jobs. Fine Tuning Jobs Status After the fine tuning job is completed, the fine-tuned model will appear in "Models" with a prefix of "ft:" and is ready to be used by the completion API or as part of an SGP application. Fine-Tuned Model ## Using the API You can also create new fine-tuning jobs directly using the SGP API, for details please refer to the [API Reference](/reference/fine-tuning-jobs-v3-beta/create-fine-tuning-job).