If a model on the Hub is tied to a supported library, loading the model can be done in just a few lines. For information on accessing the model, you can click on the “Use in Library” button on the model page to see how to do so. For example,
distilgpt2 shows how to do so with 🤗 Transformers below.
Using the Hugging Face Client Library
You can use the
huggingface_hub library to create, delete, update and retrieve information from repos. You can also download files from repos or integrate them into your library! For example, you can quickly load a Scikit-learn model with a few lines.
from huggingface_hub import hf_hub_download import joblib REPO_ID = "YOUR_REPO_ID" FILENAME = "sklearn_model.joblib" model = joblib.load( hf_hub_download(repo_id=REPO_ID, filename=FILENAME) )
Since all models on the Model Hub are Git repositories, you can clone the models locally by running:
git lfs install git clone <MODEL URL>
If you have write-access to the particular model repo, you’ll also have the ability to commit and push revisions to the model.