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:
- 921c2cf3aea70252928e9ed243799e4a2b8fe255403059257234cde398084036
- Size of remote file:
- 4.41 MB
- SHA256:
- 3ae00eb32f11155ccb9ab7d61d333182e380bb1b35dd5fff1e5f04c52afbf9c6
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