Instructions to use Arigadam/img2float with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Arigadam/img2float with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Arigadam/img2float") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ec65d42812f307fb7e8be3d448dafa297c9bef9038c248f970986435c903c1f
- Size of remote file:
- 51.4 kB
- SHA256:
- b0c49d99a3ea40d87df53494990c249a3fc9a768461af2ebe9e188606560e971
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