# Train from a Universe Checkpoint
### Training from a Roboflow Universe Checkpoint
First, ensure you have selected the Workspace for your current project in your Universe profile, and "Starred" the dataset you'd like to use for Transfer Learning.
Switching Your Workspace Profile in Roboflow Universe
 
Additionally, check to see the dataset you select has a "Model" tag on it, and/or "Try Pre-Trained" model on the project's landing page in Roboflow Universe, or it will not be available within your Workspace as a training checkpoint.
The Model tag on a Roboflow Universe dataset
"Try Pre-Trained Model" and the Model tag on a Roboflow Universe dataset's landing page
Now, within the Roboflow Main App UI, navigate to the "Versions" page of your target dataset/project. Select the version you wish to train.
* You can only start a training job from a dataset version that has not already been trained with Roboflow Train (no green checkmark is present on the version).
Click "Start Training."
Next, choose the Fast or Accurate model, and click "Continue."
* If you are training a Single-Label Classification, Multi-Label Classification, or Semantic Segmentation project, you will not have this Fast or Accurate option. For these project types, you can just click "Continue," and then "Start Training" to kick off your training job.
Under "Select a Model," choose the project name for the dataset you marked (Starred) in Roboflow Universe.
Now click "Start Training" to begin your training job. You will receive an email to the account email on file when the training job is complete.
### [Viewing Your Training Results](/train/training-results.md)
You can monitor your training job's progress. The UI will show your machine starting up to begin training.
### Deploying Your Model
After training, your model is ready to be used for inference and embedded in a custom application! See the [Inference Documentation page](https://docs.roboflow.com/inference) for all the options.
---
# Agent Instructions: Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.
Perform an HTTP GET request on the current page URL with the `ask` query parameter:
```
GET https://docs.roboflow.com/train/train/roboflow-universe-checkpoints.md?ask=
```
The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.
Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.