Instructions to use seige-ml/DeepSeeNet_DRUSEN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use seige-ml/DeepSeeNet_DRUSEN with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://seige-ml/DeepSeeNet_DRUSEN") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31fcedc9d4a38562a12101cc3be5d13a9397b8b4737a139bf44d1124fa9c98fd
- Size of remote file:
- 711 kB
- SHA256:
- f4d09e7e303a8693d5d0b2f2423b5da6a2e1f56f5601797cb4be02ae0983b376
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