Instructions to use FPSica/beyond-backscatter-grd-gee with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use FPSica/beyond-backscatter-grd-gee with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://FPSica/beyond-backscatter-grd-gee") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d7ac6c9a00d74ee725d773ec3b7a313f47bc1dc815686128dfb99e34dae42c09
- Size of remote file:
- 32.7 MB
- SHA256:
- 658845000dd1cbdb34a626850cef41906fa003ff72235f27646148f2af129339
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