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:
- 280f2b5b0be4b42dca54dc864ecc2328850171f3722ea394040126f15469966d
- Size of remote file:
- 29 kB
- SHA256:
- 8ca36dae5d3d62d2bfc9a67654aae9abb745422f2a0c2fb70208801db059aa3a
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