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:
- f2e650361b29ac63137698f2305b6b926c3721ba2da2cf81c5de2def043d8b84
- Size of remote file:
- 54 Bytes
- SHA256:
- 97de84a998b49af6a3a79988ef56908c5ad4741d1c5a315652f366c131cc3a8a
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