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Fix error (#5660)
# Description <!-- Please include a summary of the changes and the related issue. Please also include relevant motivation and context. List any dependencies that are required for this change. --> Closes #<issue_number> **Type of change** <!-- Please delete options that are not relevant. Remember to title the PR according to the type of change --> - Bug fix (non-breaking change which fixes an issue) - New feature (non-breaking change which adds functionality) - Breaking change (fix or feature that would cause existing functionality to not work as expected) - Refactor (change restructuring the codebase without changing functionality) - Improvement (change adding some improvement to an existing functionality) - Documentation update **How Has This Been Tested** <!-- Please add some reference about how your feature has been tested. --> **Checklist** <!-- Please go over the list and make sure you've taken everything into account --> - I added relevant documentation - I followed the style guidelines of this project - I did a self-review of my code - I made corresponding changes to the documentation - I confirm My changes generate no new warnings - I have added tests that prove my fix is effective or that my feature works - I have added relevant notes to the CHANGELOG.md file (See https://keepachangelog.com/)
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argilla/docs/getting_started/quickstart.md

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@@ -85,7 +85,7 @@ Congrats! Your Argilla server is ready to start your first project.
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The quickest way to start exploring the tool and create your first dataset is by importing an exiting one from the Hugging Face Hub.
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To do this, log in to the Argilla UI and in the Home page click on "Import from Hub". You can choose one of the sample datasets or paste a repo id in the input. This will look something like `stanfordnlp/imdb`.
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To do this, log in to the Argilla UI and in the Home page click on "Import dataset from Hugging Face". You can choose one of the sample datasets or paste a repo id in the input. This will look something like `stanfordnlp/imdb`.
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Argilla will automatically interpret the columns in the dataset to map them to Fields and Questions.
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