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:
- dce5ded3aead7be9c64da149eb86d7156593750ddb39b773f2a5a51c94b46e62
- Size of remote file:
- 56 Bytes
- SHA256:
- 52437f7abba1242624c0f97fb6253427616afbcc8a0f6e9e0f641425cd7c204f
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