Instructions to use WheelsTransit/HK-TransitFlow-Net with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use WheelsTransit/HK-TransitFlow-Net with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://WheelsTransit/HK-TransitFlow-Net") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 163545289e2391d6c7cbb1d8644624e5660df83ac22bd80b30b96f268c4700df
- Size of remote file:
- 1.59 MB
- SHA256:
- 2e2e279a857f60e9c5990e88bccc3cdabedb25fbc1ab227644c2334b75504fa6
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