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Using Keras at Hugging Face
Using Keras at Hugging Face
Keras is an open-source multi-backend deep learning framework, with support for JAX, TensorFlow, and PyTorch. You can find more details about it on keras.io.
Exploring Keras in the Hub
You can list keras models on the Hub by filtering by library name on the models page.
Keras models on the Hub come up with useful features when uploaded directly from the Keras library:
- A generated model card with a description, a plot of the model, and more.
- A download count to monitor the popularity of a model.
- A code snippet to quickly get started with the model.
Using existing models
Keras is deeply integrated with the Hugging Face Hub. This means you can load and save models on the Hub directly from the library. To do that, you need to install a recent version of Keras and huggingface_hub. The huggingface_hub library is a lightweight Python client used by Keras to interact with the Hub.
pip install -U keras huggingface_hubOnce you have the library installed, you just need to use the regular keras.saving.load_model method by passing as argument a Hugging Face path. An HF path is a repo_id prefixed by hf:// e.g. "hf://keras-io/weather-prediction". Read more about load_model in Keras documentation.
import keras
model = keras.saving.load_model("hf://Wauplin/mnist_example")If you want to see how to load a specific model, you can click Use this model on the model page to get a working code snippet!
Sharing your models
Similarly to load_model, you can save and share a keras model on the Hub using model.save() with an HF path:
model = ...
model.save("hf://your-username/your-model-name")If the repository does not exist on the Hub, it will be created for you. The uploaded model contains a model card, a plot of the model, the metadata.json and config.json files, and a model.weights.h5 file containing the model weights.
By default, the repository will contain a minimal model card. Check out the Model Card guide to learn more about model cards and how to complete them. You can also programmatically update model cards using huggingface_hub.ModelCard (see guide).
You might be already familiar with .keras files. In fact, a .keras file is simply a zip file containing the .json and model.weights.h5 files. When pushed to the Hub, the model is saved as an unzipped folder in order to let you navigate through the files. Note that if you manually upload a .keras file to a model repository on the Hub, the repository will automatically be tagged as keras but you won’t be able to load it using keras.saving.load_model.