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:
- bb1518f24e8c70785396220056d1e34c35468b1a49a7ee0fd6c14a68a9a6e9fb
- Size of remote file:
- 245 kB
- SHA256:
- 804b83f20756b61c12c91f766d5f1cbf479f612b789a39bbb386242a1d57bd12
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