documentation-images
VerifiedImages used in Hugging Face library documentation.
What is documentation-images?
The dataset consists of images sourced directly from Hugging Face library documentation pages.
It supports reference needs for documentation maintainers and contributors working with Hugging Face tools.
What you can build with documentation-images
Testing image loading pipelines
Load the images to verify basic vision data handling and preprocessing steps in Hugging Face datasets workflows.
Creating documentation examples
Reference the assets when building tutorials or READMEs that demonstrate Hugging Face library features.
Demoing lightweight vision datasets
Use the small collection for quick prototypes or sanity checks before scaling to larger annotated datasets.
Load documentation-images
from datasets import load_dataset
ds = load_dataset("huggingface/documentation-images")- 1Install the datasets library with pip install datasets
- 2Import load_dataset from the datasets package
- 3Call load_dataset('huggingface/documentation-images')
- 4Inspect the returned DatasetDict and access image columns
- 5Iterate over samples for local inspection or further processing
documentation-images: pros & cons
Pros
- +Official Hugging Face curated assets
- +Lightweight with under 1,000 images
- +Directly loadable via the datasets library
- +Ready-made visual examples from real library docs
Cons
- –No task labels or annotations provided
- –Not intended for model training or benchmarking
- –Limited scale and diversity by design
Frequently asked questions
A collection of fewer than 1,000 images used in Hugging Face library documentation.
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