# End-of-chapter quiz[[end-of-chapter-quiz]]

Let's test what you learned in this chapter!

### 1. What can you use Gradio to do?

share=True parameter in the launch method, you can generate a share link to send to anyone.",
            correct: true
		},
		{
			text: "Debug your model",
			explain: "One advantage of a gradio demo is being able to test your model with real data which you can change and observe the model's predictions change in real time, helping you debug your model.",
			correct: true
		},
		{
			text: "Train your model",
			explain: "Gradio is designed to be used for model inference, AFTER your model is trained.",
		}
	]}
/>

### 2. Gradio ONLY works with PyTorch models

### 3. Where can you launch a Gradio demo from?

### 4. Gradio is designed primarily for NLP models

### 5. Which of the following features are supported by Gradio?

gr.Interface.load() method",
			correct: true
        }
	]}
/>

### 6. Which of the following are valid ways of loading a Hugging Face model from Hub or Spaces?

### 7. Select all the steps necessary for adding state to your Gradio interface

### 8. Which of the following are components included in the Gradio library?

### 9. What does Gradio `Blocks` allow you to do?

### 10. You can share a public link to a `Blocks` demo and host a `Blocks` demo on Hugging Face spaces.