TF-Keras (legacy)
tf-keras
is the name given to Keras 2.x version. It is now hosted as a separate GitHub repo here. Though it’s a legacy framework, there are still 4.5k+ models hosted on the Hub. These models can be loaded using the huggingface_hub
library. You must have either tf-keras
or keras<3.x
installed on your machine.
If you are interested in Keras 3.x support, check out this guide.
Once installed, you just need to use the from_pretrained_keras
method to load a model from the Hub. Read more about from_pretrained_keras
here.
from huggingface_hub import from_pretrained_keras
model = from_pretrained_keras("keras-io/mobile-vit-xxs")
prediction = model.predict(image)
prediction = tf.squeeze(tf.round(prediction))
print(f'The image is a {classes[(np.argmax(prediction))]}!')
# The image is a sunflower!
You can also host your tf-keras
model on the Hub. However, keep in mind that tf-keras
is a legacy framework. To reach a maximum number of users, we recommend to create your model using Keras 3.x and share it natively as described above. For more details about uploading tf-keras
models, check out push_to_hub_keras
documentation.
from huggingface_hub import push_to_hub_keras
push_to_hub_keras(model,
"your-username/your-model-name",
"your-tensorboard-log-directory",
tags = ["object-detection", "some_other_tag"],
**model_save_kwargs,
)
Additional resources
- Blog post Putting Keras on 🤗 Hub for Collaborative Training and Reproducibility (April 2022)