Instructions to use Jabka/digits with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Jabka/digits 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://Jabka/digits") - Notebooks
- Google Colab
- Kaggle
Download keras_metadata.pb from Jabka/digits: direct link, hf CLI and curl.
- Browser
- Download file 12.6 kB
-
https://huggingface.co/Jabka/digits/resolve/main/keras_metadata.pb
- Command line
-
hf download hf://Jabka/digits/keras_metadata.pb
-
curl -L -o keras_metadata.pb https://huggingface.co/Jabka/digits/resolve/main/keras_metadata.pb
12.6 kB
- Xet hash:
- d9726700d251536b67d22e248067bbb6c0d598e7fec8ad337afb9a0e562609bf
- Size of remote file:
- 12.6 kB
- SHA256:
- 70886eabed6b7c965375f533b4aa3f9e9b613f8ec4665d51c81fc02419633944
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