At Hugging Face, we are on a mission to democratize good Machine Learning and we believe in the value of open source. That’s why we designed 🤗 Datasets so that anyone can share a dataset with the greater ML community. There are currently thousands of datasets in over 100 languages in the Hugging Face Hub, and the Hugging Face team always welcomes new contributions!
Dataset repositories offer features such as:
This guide will show you how to share a dataset that can be easily accessed by anyone.
You can share your dataset with the community with a dataset repository on the Hugging Face Hub. It can also be a private dataset if you want to control who has access to it.
In a dataset repository, you can either host all your data files and/or use a dataset script.
The dataset script is optional if your dataset is in one of the following formats: CSV, JSON, JSON lines, text or Parquet.
The script also supports many kinds of compressed file types such as: GZ, BZ2, LZ4, LZMA or ZSTD.
For example, your dataset can be made of .json.gz
files.
On the other hand, if your dataset is not in a supported format or if you want more control over how your dataset is loaded, you can write your own dataset script.
When loading a dataset from the Hub:
For more information on how to load a dataset from the Hub, take a look at the load a dataset from the Hub tutorial.
Sharing a community dataset will require you to create an account on hf.co if you don’t have one yet. You can directly create a new dataset repository from your account on the Hugging Face Hub, but this guide will show you how to upload a dataset from the terminal.
huggingface-cli login
huggingface-cli repo create your_dataset_name --type dataset
Add the -organization
flag to create a repository under a specific organization:
huggingface-cli repo create your_dataset_name --type dataset --organization your-org-name
# Make sure you have git-lfs installed
# (https://git-lfs.github.com/)
git lfs install
git clone https://huggingface.co/datasets/namespace/your_dataset_name
Here the namespace
is either your username or your organization name.
README.md
is a Dataset card that describes the datasets contents, creation, and usage. To write a Dataset card, see the dataset card page.
The raw data files of the dataset (optional, if they are hosted elsewhere you can specify the URLs in the dataset script). If you don’t need a dataset script, you can take a look at how to structure your dataset repository for your data files.
your_dataset_name.py
is your dataset loading script (optional if your data files are already in the supported formats csv/jsonl/json/parquet/txt). To create a dataset script, see the dataset script page.
You can directly upload your files from your repository on the Hugging Face Hub, but this guide will show you how to upload the files from the terminal.
git lfs track
or else you will encounter an error later when you push your files:cp /somewhere/data/*.json .
git lfs track *.json
git add .gitattributes
git add *.json
git commit -m "add json files"
cp /somewhere/data/README.md .
cp /somewhere/data/load_script.py .
git add --all
git status
git commit -m "First version of the your_dataset_name dataset."
git push
Congratulations, your dataset has now been uploaded to the Hugging Face Hub where anyone can load it in a single line of code! 🥳
dataset = load_dataset("namespace/your_dataset_name")
If you need help with a dataset script, feel free to check the datasets forum: it’s possible that someone had similar issues and shared how they managed to fix them.
Then if your script is ready and if you wish your dataset script to be reviewed by the Hugging Face team, you can open a discussion in the Community tab of your dataset with this message:
# Dataset rewiew request for <Dataset name>
## Description
<brief description of the dataset>
## Files to review
- file1
- file2
- ...
cc @lhoestq @polinaeterna @mariosasko @albertvillanova
Members of the Hugging Face team will be happy to review your dataset script and give you advice.
Datasets used to be hosted on our GitHub repository, but all datasets have now been migrated to the Hugging Face Hub. The legacy GitHub datasets were added originally on our GitHub repository and therefore don’t have a namespace: “squad”, “glue”, etc. unlike the other datasets that are named “username/dataset_name” or “org/dataset_name”. Those datasets are still maintained on GitHub, and if you’d like to edit them, please open a Pull Request on the huggingface/datasets repository. Sharing your dataset to the Hub is the recommended way of adding a dataset.
The distinction between a Hub dataset and a dataset from GitHub only comes from the legacy sharing workflow. It does not involve any ranking, decisioning, or opinion regarding the contents of the dataset itself.
The code of these datasets are reviewed by the Hugging Face team, and they require test data in order to be regularly tested.
In some rare cases it makes more sense to open a PR on GitHub. For example when you are not the author of the dataset and there is no clear organization / namespace that you can put the dataset under.
For more info, please take a look at the documentation on How to add a new dataset in the huggingface/datasets repository.