# ML Models Spice Models enable the training and use of ML models natively on the Spice platform. The platform currently supports time-series forecasting models, with other categories of models planned. Hosted models have first-class access to co-located data for training and inferencing including: [Spice managed datasets](broken://pages/JnKPswDs1OXhUD2OxR0K), [user managed datasets](https://github.com/spicehq/docs/blob/trunk/portal/external-data-sources.md), and [custom datasets and views](https://github.com/spicehq/docs/blob/trunk/portal/datasets-and-views.md). Additionally, [Spice Firecache](/features/federated-sql-query.md) can be leveraged to train and infer up to 10x faster. ### Defining a Model Models are defined using a [model manifest](broken://pages/kBNlZsrTXSmL6zaiY8bm) YAML file. Model details such as data requirements, architecture, training parameters, and other important hyperparameters are defined in the `model.yaml.` Add a `model.yaml` file to the repository path `/models/[model_name]/model.yaml` of a [GitHub connected Spice app](https://github.com/spicehq/docs/blob/trunk/portal/apps/connect-github.md), replacing `[model_name]` with the desired model name. Refer to the [Models YAML specification](broken://pages/kBNlZsrTXSmL6zaiY8bm) for all available configuration options. For example model manifests, see the [models samples repo](https://github.com/spiceai/samples/tree/trunk/.spice/models). ## Training a Model In the [spice.ai Portal](/content/site-root.html), navigate to the **Models** tab of the Spice app. `model.yaml` files committed to the connected repository will be automatically detected and imported as Spice Models.

Spice Models defined in `model.yaml` files automatically detected and imported in the Portal.

Navigating to a specific Model will show detailed information as defined in the `model.yaml`. A training run can be started using the **Train** button.

**Training runs** in progress will be shown and updated, along with historical training runs.

The **Training Status** will be updated to `Complete` for successfully completed training runs. Details and the Training Report are available on the **Training Run** page.

A successfully completed Model training run with status "Complete".

### Running Model Predictions A successfully trained model can be used to make predictions. The lookback data (inferencing data) is automatically provided by the platform and wired up to the inference, enabling a prediction to be made using a simple API call. ### AI Predictions in the Playground Navigate to **AI Predictions** in the **Playground**. Successfully trained models will be available for selection from the model selector drop down on the right. Clicking **Predict** will demonstrate calling the predictions API using lookback data within the Spice platform. A graph of the predicted value(s) along with the lookback data will be displayed.

### Predictions by API The **Training Runs** page provides training details including a copyable `curl` command to make a prediction from the command line. For details on the API, see [Prediction Documentation](broken://pages/2C09l89bwNrM5jRF0xSx).