Buckets:
| # Datasets | |
| ๐ค Datasets is a library for easily accessing and sharing AI 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 and streaming 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. | |
| <a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="./tutorial" | |
| >Tutorials | |
| Learn the basics and become familiar with loading, accessing, and processing a dataset. Start here if you are using ๐ค Datasets for the first time! | |
| <a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="./how_to" | |
| >How-to guides | |
| Practical guides to help you achieve a specific goal. Take a look at these guides to learn how to use ๐ค Datasets to solve real-world problems. | |
| <a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="./about_arrow" | |
| >Conceptual guides | |
| High-level explanations for building a better understanding about important topics such as the underlying data format, the cache, and how datasets are generated. | |
| <a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="./package_reference/main_classes" | |
| >Reference | |
| Technical descriptions of how ๐ค Datasets classes and methods work. | |
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