Instructions to use Eakempreet/ATAS-models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Eakempreet/ATAS-models with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Eakempreet/ATAS-models") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ecad28103f9119aa67aa98275c4b8ce0fac2e9f523d2a9ea33056ee4f855de7d
- Size of remote file:
- 942 MB
- SHA256:
- f35c73c33c0318b07ec261f6d1cf37e5ce15543a32867a398841793c9f1fca2d
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