# Dreambooth Guide
You can open **Dreambooth** tab, by combining the use with native Dreambooth, the tab **Create from Cloud** and **Select from Cloud** that newly added by the solution, you can achieve  cloud-based model creating and training in Dreambooth.


## Create Model
1. Open **Dreambooth** tab, **Model** subtab **Create From Cloud**.
![Creat model tab](../images/open-create-model-tab.png)
2. Enter a model name in the **Name** text box.

    !!! Important "Notice"
        Please note the naming format requirements: the name can only contain alphanumeric characters and dashes ("-").

3. Select one checkpoint under **Source Checkpoint** dropdown list.
> **Note：** The checkpoint files here include two sources: files starting with "local" are locally stored checkpoint files, while those starting with "cloud" are checkpoint files stored on Amazon S3. For first-time use, it is recommended to select a local checkpoint file.
![Select checkpoint](../images/select-checkpoint.png)
4. Click **Create Model From Cloud** to start model creation on cloud. **Model Creation Jobs Details** field will instantly update with the progress of the model creation job. When the status changes to *Complete*, it indicates that the model creation is finished.

## Train Model
1. Open **Dreambooth** tab, **Model** subtab, **Select From Cloud**.
2. Fresh and select the model from **Model** dropd down list that need to train.
3. Set corresponding parameters in **Input** session.
4. Click **SageMaker Train** to start model training task. The **Training Job Details** section will be updated in real-time with the status of the model training job. When the status changes to *Complete*, an email notification will be sent to the email address provided during the initial deployment of the solution, indicating that the model training is complete.
5. Future steps. For example: Navigate to **txt2img** tab **Amazon SageMaker Inference** panel, check trained model by refreshing **Stable Diffusion Checkpoint** dropdown list.