Instructions to use PrathameshRaut/apvclassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use PrathameshRaut/apvclassifier with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://PrathameshRaut/apvclassifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a7305f41664d578430da08dcf2d28602cfc5fb4e3615c67cf642591a7f49d637
- Size of remote file:
- 72.7 MB
- SHA256:
- c0645c6b1e4def291fc484ac9e466ad37ffb4aa74f9f4b24334ebde2b5aa5495
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