Instructions to use seige-ml/DeepSeeNet_CGA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use seige-ml/DeepSeeNet_CGA 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_CGA") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc2b45211e340813e55d6eb52cf9b00f11be9073e4af8db7123568d5a55676f6
- Size of remote file:
- 57 Bytes
- SHA256:
- 511dfcef26868b4a09e54b093e80360e9e10fbb8932e7f8cdc9d5738f5cdaaa1
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