Instructions to use aegishield/idpred with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use aegishield/idpred 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/idpred") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ae7191d37b2e295d0155dd381257705d162452e235a5245f357bccaafe442fd
- Size of remote file:
- 57 Bytes
- SHA256:
- 394d99d9df162099393e2f642b11ec3ba0a70fc652ce0a8862536df7848af8a3
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