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:
- 5b44964f4ed39db2188286913428e37901fb9dcf6ff695da5e333588eacb66b6
- Size of remote file:
- 29.1 kB
- SHA256:
- 8e439e1fe8b9d0720868d901fa010e50a39161ba1623ff407b8fdc45e3d58b94
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