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- Uploading a dataset to the hub.

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In this video, we'll take a look

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at how you can upload
your very own dataset

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to the Hugging Face Hub.

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The first thing you need to do

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is create a new dataset
repository on the hub.

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So, just click on your profile icon

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and select the New Dataset button.

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Next, we need to assign
an owner of the dataset.

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By default, this will be your hub account,

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but you can also create datasets

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under any organization that you belong to.

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Then, we just need to give
the dataset a good name

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and specify whether it is a
public or private dataset.

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Public datasets can be accessed by anyone

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while private datasets
can only be accessed

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by you or members of your organization.

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And with that, we can go
ahead and create the dataset.

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Now that you have an empty
dataset repository on the hub,

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the next thing to do is
add some actual data to it.

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You can do this with git,

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but the easiest way is by
selecting the Upload file button.

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And then, you can just go ahead

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and upload the files
directly from your machine.

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After you've uploaded your files,

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you'll see them appear in the repository

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under the Files and versions tab.

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The last step is to create a dataset card.

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Well-documented datasets
are more likely to be useful

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to others as they provide
the context to decide

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whether the dataset is relevant

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or whether there are any biases

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or risks associated
with using the dataset.

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On the Hugging Face Hub,

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this information is stored in
each repositories README file.

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There are two main steps
that you should take.

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First, you need to create some metadata

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that will allow your dataset

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to be easily found by others on the hub.

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You can create this metadata

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using the datasets tagging application,

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which we'll link to in
the video description.

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Once you've created the metadata,

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you can fill out the
rest of the dataset card,

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and we provide a template

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that we'll also link to in the video.

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And once your dataset is on the hub,

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you can load it using the
trusty load_dataset function.

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Just provide the name of your repository

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and a data_files argument,
and you're good to go.

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