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 }, ]} />