Instructions to use Okneas/digits with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Okneas/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://Okneas/digits") - Notebooks
- Google Colab
- Kaggle
Download keras_metadata.pb from Okneas/digits: direct link, hf CLI and curl.
- Browser
- Download file 12.5 kB
-
https://huggingface.co/Okneas/digits/resolve/main/keras_metadata.pb
- Command line
-
hf download hf://Okneas/digits/keras_metadata.pb
-
curl -L -o keras_metadata.pb https://huggingface.co/Okneas/digits/resolve/main/keras_metadata.pb
12.5 kB
- Xet hash:
- 2971d7594083804edcfd8c60784236a94c5ae45310e5f5737a8a7b234214f9aa
- Size of remote file:
- 12.5 kB
- SHA256:
- 860cf6015cd5753d3a760077a0cf3e3277001ee7980c8f49671110d0229d569a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.