Instructions to use kadasterdst/wrz-prod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use kadasterdst/wrz-prod 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/wrz-prod") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from kadasterdst/wrz-prod: direct link, hf CLI and curl.
- Browser
- Download file 1.36 MB
-
https://huggingface.co/kadasterdst/wrz-prod/resolve/main/saved_model.pb
- Command line
-
hf download hf://kadasterdst/wrz-prod/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/kadasterdst/wrz-prod/resolve/main/saved_model.pb
1.36 MB
- Xet hash:
- 374c3d1b41eb5447835fac693517d2e062ff6abf085f67ab648a0116a3a4da89
- Size of remote file:
- 1.36 MB
- SHA256:
- 39c86c6fd5013261973be730dc829ca95f321de4f8dd1a5b67578488e1627ceb
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