course/pr_1213/en/chapter10/7.md

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

Let's test what you learned in this chapter!

### 1. What can you use Argilla for?

### 2. Argilla ONLY works in the Hugging Face Spaces and with Hugging Face Datasets.

### 3. You need a Hugging Face token to connect the Python SDK to your Argilla server.

### 4. What are **fields** in Argilla? How many fields can you use?

### 5. What's the best type of question for a token classification task?

### 6. What is the purpose of the "Save as draft" button?

### 7. Argilla does not offer suggested labels automatically, you need to provide that data yourself.

### 8. Select all the necessary steps to export an Argilla dataset in full to the Hub:

client= rg.Argilla(api_url='...', api_key='...')",
			explain: "Yes, to interact with your server you'll need to instantiate it first.",
            correct: true
        },
		{
			text: "Import the dataset from the hub: dataset = rg.Dataset.from_hub(repo_id='argilla/ag_news_annotated')",
			explain: "No. This is to import a dataset from the Hub into your Argilla instance.",
        },
        {
			text: "Load the dataset: dataset = client.datasets(name='my_dataset')",
			explain: "Yes, you'll need this for further operations",
			correct: true
        },
        {
			text: "Convert the Argilla dataset into a Datasets dataset: dataset = dataset.to_datasets()",
			explain: "This is not needed if you export the full dataset. Argilla will take care of this for you. However, you might need it if you're working with a subset of records."
        },
        {
			text: "Use the to_hub method to export the dataset: dataset.to_hub(repo_id='my_username/dataset_name')",
			explain: "This will push the dataset to the indicated repo id, and create a new repo if it doesn't exist.",
            correct: true
        },
	]}
/>