# Datasets

<img class="float-left !m-0 !border-0 !dark:border-0 !shadow-none !max-w-lg w-[150px]" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/datasets/datasets_logo.png"/>

🤗 Datasets is a library for easily accessing and sharing datasets for Audio, Computer Vision, and Natural Language Processing (NLP) tasks.

Load a dataset in a single line of code, and use our powerful data processing methods to quickly get your dataset ready for training in a deep learning model. Backed by the Apache Arrow format, process large datasets with zero-copy reads without any memory constraints for optimal speed and efficiency. We also feature a deep integration with the [Hugging Face Hub](https://huggingface.co/datasets), allowing you to easily load and share a dataset with the wider machine learning community.

Find your dataset today on the [Hugging Face Hub](https://huggingface.co/datasets), and take an in-depth look inside of it with the live viewer.

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    <a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="./tutorial"
      ><div class="w-full text-center bg-gradient-to-br from-blue-400 to-blue-500 rounded-lg py-1.5 font-semibold mb-5 text-white text-lg leading-relaxed">Tutorials</div>
      <p class="text-gray-700">Learn the basics and become familiar with loading, accessing, and processing a dataset. Start here if you are using 🤗 Datasets for the first time!</p>
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    <a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="./how_to"
      ><div class="w-full text-center bg-gradient-to-br from-indigo-400 to-indigo-500 rounded-lg py-1.5 font-semibold mb-5 text-white text-lg leading-relaxed">How-to guides</div>
      <p class="text-gray-700">Practical guides to help you achieve a specific goal. Take a look at these guides to learn how to use 🤗 Datasets to solve real-world problems.</p>
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    <a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="./about_arrow"
      ><div class="w-full text-center bg-gradient-to-br from-pink-400 to-pink-500 rounded-lg py-1.5 font-semibold mb-5 text-white text-lg leading-relaxed">Conceptual guides</div>
      <p class="text-gray-700">High-level explanations for building a better understanding about important topics such as the underlying data format, the cache, and how datasets are generated.</p>
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    <a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="./package_reference/main_classes"
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      <p class="text-gray-700">Technical descriptions of how 🤗 Datasets classes and methods work.</p>
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