# Models
{% hint style="info" %}
*Check-out the walk-through on how to save and load a DSL Model.*
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Saving and loading a model
Once the Notebook script is executed successfully, the users can save them as a model. The saved model can be loaded into the Notebook.
## Saving a Data Science Lab Model
* Navigate to a Notebook.
* Write code using the following sequence:
* Read DataFrame
* Define test and train data
* Create a model
* Execute the script.
Sample Script for a Data Science Model
* Get a new cell.
* Give a model name to specify the model.
* Execute the cell.
* After the code gets executed, click the ***Save Model*** notebook in a new cell.
* The saved model gets listed under the ***Models*** list.
### **Function Parameters**
* Model - Trained model variable name.
* ModelName - Desired name given by user for the trained model.
* ModelType - Type in which model can be saved.
* X - This array contains the input features or predictors used to train the model. Each row in the X\_train array represents a sample or observation in the training set, and each column represents a feature or variable.
* y - This array contains the corresponding output or response variable for each sample in the training set. It is also called the target variable, dependent variable, or label. The y\_train array has the same number of rows as the X\_train array.
* estimator\_type - The estimator\_type of a data science model refers to the type of estimator use.
Specify a Data Science Lab Model by giving a name
## Loading a Data Science Lab Model
* Click on a new cell and select the model by using the given checkbox to load it.
* The model gets loaded into a new cell.
Loading a saved Data Science Lab Model
{% hint style="info" %}
*Please Note: Refer the **Data Science Lab Quick Start Flow** page to get an overview of the **Data Science Lab** module in nutshell.* [***Click here***](/data-science-lab-1/data-science-lab-quick-start-flow.md) *to get redirected to the quick start flow page.*
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