Instructions to use alexvmt/CBNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use alexvmt/CBNet 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://alexvmt/CBNet") - Notebooks
- Google Colab
- Kaggle
Download model.keras from alexvmt/CBNet: direct link, hf CLI and curl.
- Browser
- Download file 215 MB
-
https://huggingface.co/alexvmt/CBNet/resolve/main/model.keras
- Command line
-
hf download hf://alexvmt/CBNet/model.keras
-
curl -L -o model.keras https://huggingface.co/alexvmt/CBNet/resolve/main/model.keras
215 MB
- Xet hash:
- 7f3e7cde6e8218ffad55bcd4637c6457400189088a49739e3d9739d500a189e3
- Size of remote file:
- 215 MB
- SHA256:
- d83fc764d8ebdf1a229dc2d83c94c779de0dbabcd79a631adb82705e7ee543d6
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