Instructions to use r48n34/test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use r48n34/test-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://r48n34/test-model") - Notebooks
- Google Colab
- Kaggle
Upload myTrainingModel.h5
Browse files- myTrainingModel.h5 +3 -0
myTrainingModel.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:483cf9d1e19e36793253b62ed30f2c7f9c7913d20cb0b07bfb813e559676ac29
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size 71677312
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