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 fingerprint.pb from Jabka/digits: direct link, hf CLI and curl.
- Browser
- Download file 56 Bytes
-
https://huggingface.co/Jabka/digits/resolve/main/fingerprint.pb
- Command line
-
hf download hf://Jabka/digits/fingerprint.pb
-
curl -L -o fingerprint.pb https://huggingface.co/Jabka/digits/resolve/main/fingerprint.pb
56 Bytes
- Xet hash:
- f02211e6d6dd1f21388f74749dc4a5d1b5539c0d6af0f99e759245eceb149abc
- Size of remote file:
- 56 Bytes
- SHA256:
- 74586a936588bda99573889e4ccba6edbc7cad52ba7a7523ea2fd1139cb2d80e
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