Instructions to use kadasterdst/idcard-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use kadasterdst/idcard-test 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://kadasterdst/idcard-test") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from kadasterdst/idcard-test: direct link, hf CLI and curl.
- Browser
- Download file 5.59 MB
-
https://huggingface.co/kadasterdst/idcard-test/resolve/refs%2Fpr%2F1/saved_model.pb
- Command line
-
hf download hf://kadasterdst/idcard-test@refs/pr/1/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/kadasterdst/idcard-test/resolve/refs%2Fpr%2F1/saved_model.pb
5.59 MB
- Xet hash:
- 457d522e9277048db9ba256feb1ea360f172229cd0cc7aeef58f8e33160fd79b
- Size of remote file:
- 5.59 MB
- SHA256:
- ab6babd14589a2cd6d4b8d0e1afe4782a159cec16bdeac04509e524482a10be9
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