Instructions to use aegishield/fingpred with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use aegishield/fingpred with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://aegishield/fingpred") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 64c61287c79376f082d584e849976764b472fe64e323e7dd4eb575363cc3caa5
- Size of remote file:
- 246 kB
- SHA256:
- b936446d4475bb56602103a02b65efe432027c73438b93ee032205e8f90e7438
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