Instructions to use hari17as/tn5000-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use hari17as/tn5000-model with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://hari17as/tn5000-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 26911b212417887669330430be2e1329da01f54086347b8a2856fd572d71083a
- Size of remote file:
- 438 kB
- SHA256:
- 21ccb62f2b2d69ae1cd6c4b81edcab1905b91d201da815d2a5168cee175bd321
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