Instructions to use septa/bird-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use septa/bird-classification with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://septa/bird-classification") - Notebooks
- Google Colab
- Kaggle
Upload saved_model (1).pb
Browse files- saved_model (1).pb +3 -0
saved_model (1).pb
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version https://git-lfs.github.com/spec/v1
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oid sha256:fa04818f7f01ad171fe6734166ce7e5c12ddece1dbc755b05351fc76e40902e3
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size 16667768
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