#
Downloading datasets

##
Integrated libraries

If a dataset on the Hub is tied to a supported library, loading the dataset can be done in just a few lines. For information on accessing the dataset, you can click on the “Use this dataset” button on the dataset page to see how to do so. For example, `samsum` shows how to do so with 🤗 Datasets below.

##
Using the Hugging Face Client Library

You can use the `huggingface_hub` library to create, delete, update and retrieve information from repos. For example, to download the `HuggingFaceH4/ultrachat_200k` dataset from the command line, run

    huggingface-cli download HuggingFaceH4/ultrachat_200k --repo-type dataset

See the huggingface-cli download documentation for more information.

You can also integrate this into your own library! For example, you can quickly load a CSV dataset with a few lines using Pandas.

    from huggingface_hub import hf_hub_download
    import pandas as pd

    REPO_ID = "YOUR_REPO_ID"
    FILENAME = "data.csv"

    dataset = pd.read_csv(
        hf_hub_download(repo_id=REPO_ID, filename=FILENAME, repo_type="dataset")
    )

##
Using Git

Since all datasets on the Hub are Git repositories, you can clone the datasets locally by running:

    git lfs install
    git clone git@hf.co:datasets/<dataset ID> # example: git clone git@hf.co:datasets/allenai/c4

If you have write-access to the particular dataset repo, you’ll also have the ability to commit and push revisions to the dataset.

Add your SSH public key to your user settings to push changes and/or access private repos.

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