Instructions to use active-learning/mnist_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use active-learning/mnist_classifier with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://active-learning/mnist_classifier") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from active-learning/mnist_classifier: direct link, hf CLI and curl.
- Browser
- Download file 104 kB
-
https://huggingface.co/active-learning/mnist_classifier/resolve/a53cd2e080d7fe2a96f76cbe0971acda044a47f8/saved_model.pb
- Command line
-
hf download hf://active-learning/mnist_classifier@a53cd2e080d7fe2a96f76cbe0971acda044a47f8/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/active-learning/mnist_classifier/resolve/a53cd2e080d7fe2a96f76cbe0971acda044a47f8/saved_model.pb
104 kB
- Xet hash:
- 1292e70790fac41af1d63993b0968d8a77caf2f28b17b1f635e9efb23553ed5d
- Size of remote file:
- 104 kB
- SHA256:
- f7c69d886c818ba7af019cb819b3ff2f8aa87ff4600d1f31415f24b27a8b27aa
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